finalform commited on
Commit
f819625
·
verified ·
1 Parent(s): 42f739a

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. .gitattributes +7 -0
  2. README.md +209 -0
  3. adapter_config.json +42 -0
  4. adapter_model.safetensors +3 -0
  5. added_tokens.json +24 -0
  6. chat_template.jinja +54 -0
  7. checkpoint-1245/README.md +209 -0
  8. checkpoint-1245/adapter_config.json +42 -0
  9. checkpoint-1245/adapter_model.safetensors +3 -0
  10. checkpoint-1245/added_tokens.json +24 -0
  11. checkpoint-1245/chat_template.jinja +54 -0
  12. checkpoint-1245/merges.txt +0 -0
  13. checkpoint-1245/optimizer.pt +3 -0
  14. checkpoint-1245/rng_state.pth +3 -0
  15. checkpoint-1245/scheduler.pt +3 -0
  16. checkpoint-1245/special_tokens_map.json +25 -0
  17. checkpoint-1245/tokenizer.json +3 -0
  18. checkpoint-1245/tokenizer_config.json +207 -0
  19. checkpoint-1245/trainer_state.json +505 -0
  20. checkpoint-1245/training_args.bin +3 -0
  21. checkpoint-1245/vocab.json +0 -0
  22. checkpoint-1660/README.md +209 -0
  23. checkpoint-1660/adapter_config.json +42 -0
  24. checkpoint-1660/adapter_model.safetensors +3 -0
  25. checkpoint-1660/added_tokens.json +24 -0
  26. checkpoint-1660/chat_template.jinja +54 -0
  27. checkpoint-1660/merges.txt +0 -0
  28. checkpoint-1660/optimizer.pt +3 -0
  29. checkpoint-1660/rng_state.pth +3 -0
  30. checkpoint-1660/scheduler.pt +3 -0
  31. checkpoint-1660/special_tokens_map.json +25 -0
  32. checkpoint-1660/tokenizer.json +3 -0
  33. checkpoint-1660/tokenizer_config.json +207 -0
  34. checkpoint-1660/trainer_state.json +668 -0
  35. checkpoint-1660/training_args.bin +3 -0
  36. checkpoint-1660/vocab.json +0 -0
  37. checkpoint-2075/README.md +209 -0
  38. checkpoint-2075/adapter_config.json +42 -0
  39. checkpoint-2075/adapter_model.safetensors +3 -0
  40. checkpoint-2075/added_tokens.json +24 -0
  41. checkpoint-2075/chat_template.jinja +54 -0
  42. checkpoint-2075/merges.txt +0 -0
  43. checkpoint-2075/optimizer.pt +3 -0
  44. checkpoint-2075/rng_state.pth +3 -0
  45. checkpoint-2075/scheduler.pt +3 -0
  46. checkpoint-2075/special_tokens_map.json +25 -0
  47. checkpoint-2075/tokenizer.json +3 -0
  48. checkpoint-2075/tokenizer_config.json +207 -0
  49. checkpoint-2075/trainer_state.json +831 -0
  50. checkpoint-2075/training_args.bin +3 -0
.gitattributes CHANGED
@@ -33,3 +33,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ checkpoint-1245/tokenizer.json filter=lfs diff=lfs merge=lfs -text
37
+ checkpoint-1660/tokenizer.json filter=lfs diff=lfs merge=lfs -text
38
+ checkpoint-2075/tokenizer.json filter=lfs diff=lfs merge=lfs -text
39
+ checkpoint-2490/tokenizer.json filter=lfs diff=lfs merge=lfs -text
40
+ checkpoint-415/tokenizer.json filter=lfs diff=lfs merge=lfs -text
41
+ checkpoint-830/tokenizer.json filter=lfs diff=lfs merge=lfs -text
42
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-Coder-14B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ ---
12
+
13
+ # Model Card for Model ID
14
+
15
+ <!-- Provide a quick summary of what the model is/does. -->
16
+
17
+
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ <!-- Provide a longer summary of what this model is. -->
24
+
25
+
26
+
27
+ - **Developed by:** [More Information Needed]
28
+ - **Funded by [optional]:** [More Information Needed]
29
+ - **Shared by [optional]:** [More Information Needed]
30
+ - **Model type:** [More Information Needed]
31
+ - **Language(s) (NLP):** [More Information Needed]
32
+ - **License:** [More Information Needed]
33
+ - **Finetuned from model [optional]:** [More Information Needed]
34
+
35
+ ### Model Sources [optional]
36
+
37
+ <!-- Provide the basic links for the model. -->
38
+
39
+ - **Repository:** [More Information Needed]
40
+ - **Paper [optional]:** [More Information Needed]
41
+ - **Demo [optional]:** [More Information Needed]
42
+
43
+ ## Uses
44
+
45
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
46
+
47
+ ### Direct Use
48
+
49
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
50
+
51
+ [More Information Needed]
52
+
53
+ ### Downstream Use [optional]
54
+
55
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
56
+
57
+ [More Information Needed]
58
+
59
+ ### Out-of-Scope Use
60
+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
62
+
63
+ [More Information Needed]
64
+
65
+ ## Bias, Risks, and Limitations
66
+
67
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
68
+
69
+ [More Information Needed]
70
+
71
+ ### Recommendations
72
+
73
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
74
+
75
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
76
+
77
+ ## How to Get Started with the Model
78
+
79
+ Use the code below to get started with the model.
80
+
81
+ [More Information Needed]
82
+
83
+ ## Training Details
84
+
85
+ ### Training Data
86
+
87
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
88
+
89
+ [More Information Needed]
90
+
91
+ ### Training Procedure
92
+
93
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
94
+
95
+ #### Preprocessing [optional]
96
+
97
+ [More Information Needed]
98
+
99
+
100
+ #### Training Hyperparameters
101
+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
103
+
104
+ #### Speeds, Sizes, Times [optional]
105
+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
107
+
108
+ [More Information Needed]
109
+
110
+ ## Evaluation
111
+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
113
+
114
+ ### Testing Data, Factors & Metrics
115
+
116
+ #### Testing Data
117
+
118
+ <!-- This should link to a Dataset Card if possible. -->
119
+
120
+ [More Information Needed]
121
+
122
+ #### Factors
123
+
124
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
125
+
126
+ [More Information Needed]
127
+
128
+ #### Metrics
129
+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
131
+
132
+ [More Information Needed]
133
+
134
+ ### Results
135
+
136
+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
141
+
142
+ ## Model Examination [optional]
143
+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
153
+
154
+ - **Hardware Type:** [More Information Needed]
155
+ - **Hours used:** [More Information Needed]
156
+ - **Cloud Provider:** [More Information Needed]
157
+ - **Compute Region:** [More Information Needed]
158
+ - **Carbon Emitted:** [More Information Needed]
159
+
160
+ ## Technical Specifications [optional]
161
+
162
+ ### Model Architecture and Objective
163
+
164
+ [More Information Needed]
165
+
166
+ ### Compute Infrastructure
167
+
168
+ [More Information Needed]
169
+
170
+ #### Hardware
171
+
172
+ [More Information Needed]
173
+
174
+ #### Software
175
+
176
+ [More Information Needed]
177
+
178
+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
181
+
182
+ **BibTeX:**
183
+
184
+ [More Information Needed]
185
+
186
+ **APA:**
187
+
188
+ [More Information Needed]
189
+
190
+ ## Glossary [optional]
191
+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
193
+
194
+ [More Information Needed]
195
+
196
+ ## More Information [optional]
197
+
198
+ [More Information Needed]
199
+
200
+ ## Model Card Authors [optional]
201
+
202
+ [More Information Needed]
203
+
204
+ ## Model Card Contact
205
+
206
+ [More Information Needed]
207
+ ### Framework versions
208
+
209
+ - PEFT 0.17.0
adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2.5-Coder-14B-Instruct",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.1,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "qalora_group_size": 16,
24
+ "r": 32,
25
+ "rank_pattern": {},
26
+ "revision": null,
27
+ "target_modules": [
28
+ "v_proj",
29
+ "up_proj",
30
+ "k_proj",
31
+ "gate_proj",
32
+ "down_proj",
33
+ "q_proj",
34
+ "o_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_dora": false,
40
+ "use_qalora": false,
41
+ "use_rslora": false
42
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:807e81c3174285d05f1d0645de6cf69db5810da702bbbc50d192e95eaa0c03aa
3
+ size 550593184
added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoint-1245/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-Coder-14B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ ---
12
+
13
+ # Model Card for Model ID
14
+
15
+ <!-- Provide a quick summary of what the model is/does. -->
16
+
17
+
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ <!-- Provide a longer summary of what this model is. -->
24
+
25
+
26
+
27
+ - **Developed by:** [More Information Needed]
28
+ - **Funded by [optional]:** [More Information Needed]
29
+ - **Shared by [optional]:** [More Information Needed]
30
+ - **Model type:** [More Information Needed]
31
+ - **Language(s) (NLP):** [More Information Needed]
32
+ - **License:** [More Information Needed]
33
+ - **Finetuned from model [optional]:** [More Information Needed]
34
+
35
+ ### Model Sources [optional]
36
+
37
+ <!-- Provide the basic links for the model. -->
38
+
39
+ - **Repository:** [More Information Needed]
40
+ - **Paper [optional]:** [More Information Needed]
41
+ - **Demo [optional]:** [More Information Needed]
42
+
43
+ ## Uses
44
+
45
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
46
+
47
+ ### Direct Use
48
+
49
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
50
+
51
+ [More Information Needed]
52
+
53
+ ### Downstream Use [optional]
54
+
55
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
56
+
57
+ [More Information Needed]
58
+
59
+ ### Out-of-Scope Use
60
+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
62
+
63
+ [More Information Needed]
64
+
65
+ ## Bias, Risks, and Limitations
66
+
67
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
68
+
69
+ [More Information Needed]
70
+
71
+ ### Recommendations
72
+
73
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
74
+
75
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
76
+
77
+ ## How to Get Started with the Model
78
+
79
+ Use the code below to get started with the model.
80
+
81
+ [More Information Needed]
82
+
83
+ ## Training Details
84
+
85
+ ### Training Data
86
+
87
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
88
+
89
+ [More Information Needed]
90
+
91
+ ### Training Procedure
92
+
93
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
94
+
95
+ #### Preprocessing [optional]
96
+
97
+ [More Information Needed]
98
+
99
+
100
+ #### Training Hyperparameters
101
+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
103
+
104
+ #### Speeds, Sizes, Times [optional]
105
+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
107
+
108
+ [More Information Needed]
109
+
110
+ ## Evaluation
111
+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
113
+
114
+ ### Testing Data, Factors & Metrics
115
+
116
+ #### Testing Data
117
+
118
+ <!-- This should link to a Dataset Card if possible. -->
119
+
120
+ [More Information Needed]
121
+
122
+ #### Factors
123
+
124
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
125
+
126
+ [More Information Needed]
127
+
128
+ #### Metrics
129
+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
131
+
132
+ [More Information Needed]
133
+
134
+ ### Results
135
+
136
+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
141
+
142
+ ## Model Examination [optional]
143
+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
153
+
154
+ - **Hardware Type:** [More Information Needed]
155
+ - **Hours used:** [More Information Needed]
156
+ - **Cloud Provider:** [More Information Needed]
157
+ - **Compute Region:** [More Information Needed]
158
+ - **Carbon Emitted:** [More Information Needed]
159
+
160
+ ## Technical Specifications [optional]
161
+
162
+ ### Model Architecture and Objective
163
+
164
+ [More Information Needed]
165
+
166
+ ### Compute Infrastructure
167
+
168
+ [More Information Needed]
169
+
170
+ #### Hardware
171
+
172
+ [More Information Needed]
173
+
174
+ #### Software
175
+
176
+ [More Information Needed]
177
+
178
+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
181
+
182
+ **BibTeX:**
183
+
184
+ [More Information Needed]
185
+
186
+ **APA:**
187
+
188
+ [More Information Needed]
189
+
190
+ ## Glossary [optional]
191
+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
193
+
194
+ [More Information Needed]
195
+
196
+ ## More Information [optional]
197
+
198
+ [More Information Needed]
199
+
200
+ ## Model Card Authors [optional]
201
+
202
+ [More Information Needed]
203
+
204
+ ## Model Card Contact
205
+
206
+ [More Information Needed]
207
+ ### Framework versions
208
+
209
+ - PEFT 0.17.0
checkpoint-1245/adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2.5-Coder-14B-Instruct",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.1,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "qalora_group_size": 16,
24
+ "r": 32,
25
+ "rank_pattern": {},
26
+ "revision": null,
27
+ "target_modules": [
28
+ "v_proj",
29
+ "up_proj",
30
+ "k_proj",
31
+ "gate_proj",
32
+ "down_proj",
33
+ "q_proj",
34
+ "o_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_dora": false,
40
+ "use_qalora": false,
41
+ "use_rslora": false
42
+ }
checkpoint-1245/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d562fdc9e85c1a745fdc16e8b2a7fa69363eabcd1afe32c16ec1ac0c67cf7003
3
+ size 550593184
checkpoint-1245/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoint-1245/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoint-1245/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1245/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:264b52a7fd6242c30e76a183e898a3e073976122edcee9bef0cb6c9964cce77f
3
+ size 1101419875
checkpoint-1245/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:62e3af0e23bf09ce130e1ead194493dd4b47fedf4ffb410929fc8cf4209f14d0
3
+ size 14645
checkpoint-1245/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:185c500d0eb013c940c5304ec0cd0b82f0001ce853aef86f81eccfc4531b38c8
3
+ size 1465
checkpoint-1245/special_tokens_map.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": "<|im_end|>"
25
+ }
checkpoint-1245/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3f9d93e80cff961819dcba7d892cf9656e086a0cf83cdbef23f10c1a493faa2
3
+ size 11422061
checkpoint-1245/tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 32768,
203
+ "pad_token": "<|im_end|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
checkpoint-1245/trainer_state.json ADDED
@@ -0,0 +1,505 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 3.0,
6
+ "eval_steps": 500,
7
+ "global_step": 1245,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.060350030175015085,
14
+ "grad_norm": 0.17640693485736847,
15
+ "learning_rate": 9.599999999999999e-05,
16
+ "loss": 1.7813,
17
+ "mean_token_accuracy": 0.6300852990150452,
18
+ "num_tokens": 156656.0,
19
+ "step": 25
20
+ },
21
+ {
22
+ "epoch": 0.12070006035003017,
23
+ "grad_norm": 0.24193964898586273,
24
+ "learning_rate": 0.00019599999999999997,
25
+ "loss": 0.9197,
26
+ "mean_token_accuracy": 0.768382026553154,
27
+ "num_tokens": 282982.0,
28
+ "step": 50
29
+ },
30
+ {
31
+ "epoch": 0.18105009052504525,
32
+ "grad_norm": 0.16499435901641846,
33
+ "learning_rate": 0.000296,
34
+ "loss": 0.5906,
35
+ "mean_token_accuracy": 0.8341364151239395,
36
+ "num_tokens": 441181.0,
37
+ "step": 75
38
+ },
39
+ {
40
+ "epoch": 0.24140012070006034,
41
+ "grad_norm": 0.23563049733638763,
42
+ "learning_rate": 0.0002999269005776963,
43
+ "loss": 0.4832,
44
+ "mean_token_accuracy": 0.8592967188358307,
45
+ "num_tokens": 567644.0,
46
+ "step": 100
47
+ },
48
+ {
49
+ "epoch": 0.30175015087507545,
50
+ "grad_norm": 0.22556591033935547,
51
+ "learning_rate": 0.0002996953705789175,
52
+ "loss": 0.3612,
53
+ "mean_token_accuracy": 0.8925437909364701,
54
+ "num_tokens": 725987.0,
55
+ "step": 125
56
+ },
57
+ {
58
+ "epoch": 0.3621001810500905,
59
+ "grad_norm": 0.33429527282714844,
60
+ "learning_rate": 0.00029930552794275785,
61
+ "loss": 0.3126,
62
+ "mean_token_accuracy": 0.9086851555109025,
63
+ "num_tokens": 853185.0,
64
+ "step": 150
65
+ },
66
+ {
67
+ "epoch": 0.4224502112251056,
68
+ "grad_norm": 0.27340370416641235,
69
+ "learning_rate": 0.0002987577849532824,
70
+ "loss": 0.2343,
71
+ "mean_token_accuracy": 0.9301495373249054,
72
+ "num_tokens": 1011232.0,
73
+ "step": 175
74
+ },
75
+ {
76
+ "epoch": 0.4828002414001207,
77
+ "grad_norm": 0.2711191475391388,
78
+ "learning_rate": 0.00029805272088449905,
79
+ "loss": 0.2021,
80
+ "mean_token_accuracy": 0.9406860828399658,
81
+ "num_tokens": 1138074.0,
82
+ "step": 200
83
+ },
84
+ {
85
+ "epoch": 0.5431502715751357,
86
+ "grad_norm": 0.19240038096904755,
87
+ "learning_rate": 0.00029719108138773827,
88
+ "loss": 0.1508,
89
+ "mean_token_accuracy": 0.9550948125123978,
90
+ "num_tokens": 1293601.0,
91
+ "step": 225
92
+ },
93
+ {
94
+ "epoch": 0.6035003017501509,
95
+ "grad_norm": 0.27221739292144775,
96
+ "learning_rate": 0.00029617377770307837,
97
+ "loss": 0.1563,
98
+ "mean_token_accuracy": 0.9542003554105759,
99
+ "num_tokens": 1418074.0,
100
+ "step": 250
101
+ },
102
+ {
103
+ "epoch": 0.663850331925166,
104
+ "grad_norm": 0.25977134704589844,
105
+ "learning_rate": 0.0002950018856956494,
106
+ "loss": 0.1228,
107
+ "mean_token_accuracy": 0.9640595990419388,
108
+ "num_tokens": 1577856.0,
109
+ "step": 275
110
+ },
111
+ {
112
+ "epoch": 0.724200362100181,
113
+ "grad_norm": 0.2311161458492279,
114
+ "learning_rate": 0.0002936766447178356,
115
+ "loss": 0.1229,
116
+ "mean_token_accuracy": 0.9646531140804291,
117
+ "num_tokens": 1704393.0,
118
+ "step": 300
119
+ },
120
+ {
121
+ "epoch": 0.7845503922751962,
122
+ "grad_norm": 0.1375264674425125,
123
+ "learning_rate": 0.0002921994562985788,
124
+ "loss": 0.0972,
125
+ "mean_token_accuracy": 0.9722524845600128,
126
+ "num_tokens": 1860935.0,
127
+ "step": 325
128
+ },
129
+ {
130
+ "epoch": 0.8449004224502112,
131
+ "grad_norm": 0.2860631048679352,
132
+ "learning_rate": 0.0002905718826611708,
133
+ "loss": 0.0853,
134
+ "mean_token_accuracy": 0.9756521546840667,
135
+ "num_tokens": 1988266.0,
136
+ "step": 350
137
+ },
138
+ {
139
+ "epoch": 0.9052504526252263,
140
+ "grad_norm": 0.11123040318489075,
141
+ "learning_rate": 0.00028879564507109946,
142
+ "loss": 0.0814,
143
+ "mean_token_accuracy": 0.9769123244285584,
144
+ "num_tokens": 2146122.0,
145
+ "step": 375
146
+ },
147
+ {
148
+ "epoch": 0.9656004828002414,
149
+ "grad_norm": 0.239139586687088,
150
+ "learning_rate": 0.0002868726220156981,
151
+ "loss": 0.0696,
152
+ "mean_token_accuracy": 0.9802538651227951,
153
+ "num_tokens": 2273996.0,
154
+ "step": 400
155
+ },
156
+ {
157
+ "epoch": 1.0,
158
+ "eval_loss": 0.07211296260356903,
159
+ "eval_mean_token_accuracy": 0.979879263285044,
160
+ "eval_num_tokens": 2354180.0,
161
+ "eval_runtime": 29.4819,
162
+ "eval_samples_per_second": 12.516,
163
+ "eval_steps_per_second": 6.275,
164
+ "step": 415
165
+ },
166
+ {
167
+ "epoch": 1.024140012070006,
168
+ "grad_norm": 0.13852086663246155,
169
+ "learning_rate": 0.0002848048472175225,
170
+ "loss": 0.0764,
171
+ "mean_token_accuracy": 0.9782544571099822,
172
+ "num_tokens": 2422077.0,
173
+ "step": 425
174
+ },
175
+ {
176
+ "epoch": 1.0844900422450212,
177
+ "grad_norm": 0.17753440141677856,
178
+ "learning_rate": 0.00028259450748355637,
179
+ "loss": 0.0527,
180
+ "mean_token_accuracy": 0.9847306323051452,
181
+ "num_tokens": 2564180.0,
182
+ "step": 450
183
+ },
184
+ {
185
+ "epoch": 1.1448400724200363,
186
+ "grad_norm": 0.13473442196846008,
187
+ "learning_rate": 0.00028024394039252005,
188
+ "loss": 0.0697,
189
+ "mean_token_accuracy": 0.9803690612316132,
190
+ "num_tokens": 2705737.0,
191
+ "step": 475
192
+ },
193
+ {
194
+ "epoch": 1.2051901025950513,
195
+ "grad_norm": 0.04998031258583069,
196
+ "learning_rate": 0.0002777556318227281,
197
+ "loss": 0.0452,
198
+ "mean_token_accuracy": 0.987179564833641,
199
+ "num_tokens": 2848782.0,
200
+ "step": 500
201
+ },
202
+ {
203
+ "epoch": 1.2655401327700664,
204
+ "grad_norm": 0.09412259608507156,
205
+ "learning_rate": 0.00027513221332311073,
206
+ "loss": 0.0615,
207
+ "mean_token_accuracy": 0.9825534737110138,
208
+ "num_tokens": 2991024.0,
209
+ "step": 525
210
+ },
211
+ {
212
+ "epoch": 1.3258901629450814,
213
+ "grad_norm": 0.12740211188793182,
214
+ "learning_rate": 0.0002723764593301788,
215
+ "loss": 0.0452,
216
+ "mean_token_accuracy": 0.9870287185907364,
217
+ "num_tokens": 3132622.0,
218
+ "step": 550
219
+ },
220
+ {
221
+ "epoch": 1.3862401931200965,
222
+ "grad_norm": 0.11777028441429138,
223
+ "learning_rate": 0.0002694912842338756,
224
+ "loss": 0.0568,
225
+ "mean_token_accuracy": 0.9838440799713135,
226
+ "num_tokens": 3273143.0,
227
+ "step": 575
228
+ },
229
+ {
230
+ "epoch": 1.4465902232951118,
231
+ "grad_norm": 0.09758122265338898,
232
+ "learning_rate": 0.0002664797392954194,
233
+ "loss": 0.0444,
234
+ "mean_token_accuracy": 0.986908946633339,
235
+ "num_tokens": 3416381.0,
236
+ "step": 600
237
+ },
238
+ {
239
+ "epoch": 1.5069402534701268,
240
+ "grad_norm": 0.0658789575099945,
241
+ "learning_rate": 0.0002633450094203953,
242
+ "loss": 0.0535,
243
+ "mean_token_accuracy": 0.9848115313053131,
244
+ "num_tokens": 3558249.0,
245
+ "step": 625
246
+ },
247
+ {
248
+ "epoch": 1.567290283645142,
249
+ "grad_norm": 0.07210762798786163,
250
+ "learning_rate": 0.000260090409790509,
251
+ "loss": 0.0409,
252
+ "mean_token_accuracy": 0.9878959685564042,
253
+ "num_tokens": 3700350.0,
254
+ "step": 650
255
+ },
256
+ {
257
+ "epoch": 1.627640313820157,
258
+ "grad_norm": 0.09006072580814362,
259
+ "learning_rate": 0.000256719382357566,
260
+ "loss": 0.052,
261
+ "mean_token_accuracy": 0.9852559435367584,
262
+ "num_tokens": 3842983.0,
263
+ "step": 675
264
+ },
265
+ {
266
+ "epoch": 1.687990343995172,
267
+ "grad_norm": 0.07121206820011139,
268
+ "learning_rate": 0.0002532354922033823,
269
+ "loss": 0.0401,
270
+ "mean_token_accuracy": 0.9882262688875199,
271
+ "num_tokens": 3985789.0,
272
+ "step": 700
273
+ },
274
+ {
275
+ "epoch": 1.748340374170187,
276
+ "grad_norm": 0.049150578677654266,
277
+ "learning_rate": 0.00024964242376947747,
278
+ "loss": 0.0514,
279
+ "mean_token_accuracy": 0.9852595126628876,
280
+ "num_tokens": 4128158.0,
281
+ "step": 725
282
+ },
283
+ {
284
+ "epoch": 1.8086904043452021,
285
+ "grad_norm": 0.08217272907495499,
286
+ "learning_rate": 0.000245943976960537,
287
+ "loss": 0.0373,
288
+ "mean_token_accuracy": 0.9887230151891708,
289
+ "num_tokens": 4270705.0,
290
+ "step": 750
291
+ },
292
+ {
293
+ "epoch": 1.8690404345202172,
294
+ "grad_norm": 0.060381677001714706,
295
+ "learning_rate": 0.00024214406312576472,
296
+ "loss": 0.051,
297
+ "mean_token_accuracy": 0.9850554609298706,
298
+ "num_tokens": 4412064.0,
299
+ "step": 775
300
+ },
301
+ {
302
+ "epoch": 1.9293904646952322,
303
+ "grad_norm": 0.07599000632762909,
304
+ "learning_rate": 0.00023824670092237557,
305
+ "loss": 0.0385,
306
+ "mean_token_accuracy": 0.9883499753475189,
307
+ "num_tokens": 4554646.0,
308
+ "step": 800
309
+ },
310
+ {
311
+ "epoch": 1.9897404948702473,
312
+ "grad_norm": 0.06878010928630829,
313
+ "learning_rate": 0.00023425601206560257,
314
+ "loss": 0.0432,
315
+ "mean_token_accuracy": 0.9873087042570114,
316
+ "num_tokens": 4688134.0,
317
+ "step": 825
318
+ },
319
+ {
320
+ "epoch": 2.0,
321
+ "eval_loss": 0.04542902857065201,
322
+ "eval_mean_token_accuracy": 0.9870176924241556,
323
+ "eval_num_tokens": 4708360.0,
324
+ "eval_runtime": 29.4629,
325
+ "eval_samples_per_second": 12.524,
326
+ "eval_steps_per_second": 6.279,
327
+ "step": 830
328
+ },
329
+ {
330
+ "epoch": 2.048280024140012,
331
+ "grad_norm": 0.07973352819681168,
332
+ "learning_rate": 0.00023017621696971407,
333
+ "loss": 0.0424,
334
+ "mean_token_accuracy": 0.9869058310371084,
335
+ "num_tokens": 4837256.0,
336
+ "step": 850
337
+ },
338
+ {
339
+ "epoch": 2.1086300543150274,
340
+ "grad_norm": 0.3017246723175049,
341
+ "learning_rate": 0.0002260116302846495,
342
+ "loss": 0.0294,
343
+ "mean_token_accuracy": 0.9908489334583283,
344
+ "num_tokens": 4969729.0,
345
+ "step": 875
346
+ },
347
+ {
348
+ "epoch": 2.1689800844900424,
349
+ "grad_norm": 0.05929604917764664,
350
+ "learning_rate": 0.0002217666563329952,
351
+ "loss": 0.0407,
352
+ "mean_token_accuracy": 0.9875844532251358,
353
+ "num_tokens": 5120477.0,
354
+ "step": 900
355
+ },
356
+ {
357
+ "epoch": 2.2293301146650575,
358
+ "grad_norm": 0.10643558949232101,
359
+ "learning_rate": 0.00021744578445212544,
360
+ "loss": 0.03,
361
+ "mean_token_accuracy": 0.9906252521276474,
362
+ "num_tokens": 5253578.0,
363
+ "step": 925
364
+ },
365
+ {
366
+ "epoch": 2.2896801448400725,
367
+ "grad_norm": 0.07998061180114746,
368
+ "learning_rate": 0.0002130535842464348,
369
+ "loss": 0.0405,
370
+ "mean_token_accuracy": 0.9873760217428207,
371
+ "num_tokens": 5406645.0,
372
+ "step": 950
373
+ },
374
+ {
375
+ "epoch": 2.3500301750150876,
376
+ "grad_norm": 0.03785248100757599,
377
+ "learning_rate": 0.0002085947007546829,
378
+ "loss": 0.0286,
379
+ "mean_token_accuracy": 0.9912718170881272,
380
+ "num_tokens": 5540521.0,
381
+ "step": 975
382
+ },
383
+ {
384
+ "epoch": 2.4103802051901027,
385
+ "grad_norm": 0.038521163165569305,
386
+ "learning_rate": 0.00020407384953756216,
387
+ "loss": 0.0402,
388
+ "mean_token_accuracy": 0.9876785135269165,
389
+ "num_tokens": 5691357.0,
390
+ "step": 1000
391
+ },
392
+ {
393
+ "epoch": 2.4707302353651177,
394
+ "grad_norm": 0.08188804239034653,
395
+ "learning_rate": 0.00019949581169068456,
396
+ "loss": 0.0286,
397
+ "mean_token_accuracy": 0.991096887588501,
398
+ "num_tokens": 5824399.0,
399
+ "step": 1025
400
+ },
401
+ {
402
+ "epoch": 2.5310802655401328,
403
+ "grad_norm": 0.07109837234020233,
404
+ "learning_rate": 0.0001948654287882601,
405
+ "loss": 0.0388,
406
+ "mean_token_accuracy": 0.9885295808315278,
407
+ "num_tokens": 5975841.0,
408
+ "step": 1050
409
+ },
410
+ {
411
+ "epoch": 2.591430295715148,
412
+ "grad_norm": 0.06275477260351181,
413
+ "learning_rate": 0.00019018759776281605,
414
+ "loss": 0.0261,
415
+ "mean_token_accuracy": 0.9916540479660034,
416
+ "num_tokens": 6108567.0,
417
+ "step": 1075
418
+ },
419
+ {
420
+ "epoch": 2.651780325890163,
421
+ "grad_norm": 0.04038365185260773,
422
+ "learning_rate": 0.00018546726572637065,
423
+ "loss": 0.0352,
424
+ "mean_token_accuracy": 0.9892910522222519,
425
+ "num_tokens": 6259991.0,
426
+ "step": 1100
427
+ },
428
+ {
429
+ "epoch": 2.712130356065178,
430
+ "grad_norm": 0.09150233864784241,
431
+ "learning_rate": 0.00018070942473853873,
432
+ "loss": 0.0255,
433
+ "mean_token_accuracy": 0.9921514791250229,
434
+ "num_tokens": 6393402.0,
435
+ "step": 1125
436
+ },
437
+ {
438
+ "epoch": 2.772480386240193,
439
+ "grad_norm": 0.04401474818587303,
440
+ "learning_rate": 0.00017591910652710262,
441
+ "loss": 0.0355,
442
+ "mean_token_accuracy": 0.9891881144046784,
443
+ "num_tokens": 6544386.0,
444
+ "step": 1150
445
+ },
446
+ {
447
+ "epoch": 2.832830416415208,
448
+ "grad_norm": 0.16860009729862213,
449
+ "learning_rate": 0.00017110137716663107,
450
+ "loss": 0.026,
451
+ "mean_token_accuracy": 0.9918778198957443,
452
+ "num_tokens": 6674740.0,
453
+ "step": 1175
454
+ },
455
+ {
456
+ "epoch": 2.8931804465902236,
457
+ "grad_norm": 0.05165860429406166,
458
+ "learning_rate": 0.0001662613317207742,
459
+ "loss": 0.0403,
460
+ "mean_token_accuracy": 0.9879327750205994,
461
+ "num_tokens": 6826652.0,
462
+ "step": 1200
463
+ },
464
+ {
465
+ "epoch": 2.9535304767652386,
466
+ "grad_norm": 0.06370134651660919,
467
+ "learning_rate": 0.00016140408885390107,
468
+ "loss": 0.0273,
469
+ "mean_token_accuracy": 0.9915495270490646,
470
+ "num_tokens": 6960481.0,
471
+ "step": 1225
472
+ },
473
+ {
474
+ "epoch": 3.0,
475
+ "eval_loss": 0.038739174604415894,
476
+ "eval_mean_token_accuracy": 0.9888446437345969,
477
+ "eval_num_tokens": 7062540.0,
478
+ "eval_runtime": 29.4618,
479
+ "eval_samples_per_second": 12.525,
480
+ "eval_steps_per_second": 6.279,
481
+ "step": 1245
482
+ }
483
+ ],
484
+ "logging_steps": 25,
485
+ "max_steps": 2490,
486
+ "num_input_tokens_seen": 0,
487
+ "num_train_epochs": 6,
488
+ "save_steps": 500,
489
+ "stateful_callbacks": {
490
+ "TrainerControl": {
491
+ "args": {
492
+ "should_epoch_stop": false,
493
+ "should_evaluate": false,
494
+ "should_log": false,
495
+ "should_save": true,
496
+ "should_training_stop": false
497
+ },
498
+ "attributes": {}
499
+ }
500
+ },
501
+ "total_flos": 5.994585574236303e+17,
502
+ "train_batch_size": 2,
503
+ "trial_name": null,
504
+ "trial_params": null
505
+ }
checkpoint-1245/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a46b0daa7fdfc376322a8afaffd8c2c7c13f904fdcef5c58858545c671ae355b
3
+ size 5969
checkpoint-1245/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1660/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-Coder-14B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ ---
12
+
13
+ # Model Card for Model ID
14
+
15
+ <!-- Provide a quick summary of what the model is/does. -->
16
+
17
+
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ <!-- Provide a longer summary of what this model is. -->
24
+
25
+
26
+
27
+ - **Developed by:** [More Information Needed]
28
+ - **Funded by [optional]:** [More Information Needed]
29
+ - **Shared by [optional]:** [More Information Needed]
30
+ - **Model type:** [More Information Needed]
31
+ - **Language(s) (NLP):** [More Information Needed]
32
+ - **License:** [More Information Needed]
33
+ - **Finetuned from model [optional]:** [More Information Needed]
34
+
35
+ ### Model Sources [optional]
36
+
37
+ <!-- Provide the basic links for the model. -->
38
+
39
+ - **Repository:** [More Information Needed]
40
+ - **Paper [optional]:** [More Information Needed]
41
+ - **Demo [optional]:** [More Information Needed]
42
+
43
+ ## Uses
44
+
45
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
46
+
47
+ ### Direct Use
48
+
49
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
50
+
51
+ [More Information Needed]
52
+
53
+ ### Downstream Use [optional]
54
+
55
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
56
+
57
+ [More Information Needed]
58
+
59
+ ### Out-of-Scope Use
60
+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
62
+
63
+ [More Information Needed]
64
+
65
+ ## Bias, Risks, and Limitations
66
+
67
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
68
+
69
+ [More Information Needed]
70
+
71
+ ### Recommendations
72
+
73
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
74
+
75
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
76
+
77
+ ## How to Get Started with the Model
78
+
79
+ Use the code below to get started with the model.
80
+
81
+ [More Information Needed]
82
+
83
+ ## Training Details
84
+
85
+ ### Training Data
86
+
87
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
88
+
89
+ [More Information Needed]
90
+
91
+ ### Training Procedure
92
+
93
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
94
+
95
+ #### Preprocessing [optional]
96
+
97
+ [More Information Needed]
98
+
99
+
100
+ #### Training Hyperparameters
101
+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
103
+
104
+ #### Speeds, Sizes, Times [optional]
105
+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
107
+
108
+ [More Information Needed]
109
+
110
+ ## Evaluation
111
+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
113
+
114
+ ### Testing Data, Factors & Metrics
115
+
116
+ #### Testing Data
117
+
118
+ <!-- This should link to a Dataset Card if possible. -->
119
+
120
+ [More Information Needed]
121
+
122
+ #### Factors
123
+
124
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
125
+
126
+ [More Information Needed]
127
+
128
+ #### Metrics
129
+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
131
+
132
+ [More Information Needed]
133
+
134
+ ### Results
135
+
136
+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
141
+
142
+ ## Model Examination [optional]
143
+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
153
+
154
+ - **Hardware Type:** [More Information Needed]
155
+ - **Hours used:** [More Information Needed]
156
+ - **Cloud Provider:** [More Information Needed]
157
+ - **Compute Region:** [More Information Needed]
158
+ - **Carbon Emitted:** [More Information Needed]
159
+
160
+ ## Technical Specifications [optional]
161
+
162
+ ### Model Architecture and Objective
163
+
164
+ [More Information Needed]
165
+
166
+ ### Compute Infrastructure
167
+
168
+ [More Information Needed]
169
+
170
+ #### Hardware
171
+
172
+ [More Information Needed]
173
+
174
+ #### Software
175
+
176
+ [More Information Needed]
177
+
178
+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
181
+
182
+ **BibTeX:**
183
+
184
+ [More Information Needed]
185
+
186
+ **APA:**
187
+
188
+ [More Information Needed]
189
+
190
+ ## Glossary [optional]
191
+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
193
+
194
+ [More Information Needed]
195
+
196
+ ## More Information [optional]
197
+
198
+ [More Information Needed]
199
+
200
+ ## Model Card Authors [optional]
201
+
202
+ [More Information Needed]
203
+
204
+ ## Model Card Contact
205
+
206
+ [More Information Needed]
207
+ ### Framework versions
208
+
209
+ - PEFT 0.17.0
checkpoint-1660/adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2.5-Coder-14B-Instruct",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.1,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "qalora_group_size": 16,
24
+ "r": 32,
25
+ "rank_pattern": {},
26
+ "revision": null,
27
+ "target_modules": [
28
+ "v_proj",
29
+ "up_proj",
30
+ "k_proj",
31
+ "gate_proj",
32
+ "down_proj",
33
+ "q_proj",
34
+ "o_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_dora": false,
40
+ "use_qalora": false,
41
+ "use_rslora": false
42
+ }
checkpoint-1660/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b608c6ab640cd93f58fa9b90499b4c68cd4f2fa6f79e0e3b614f4a061e14b778
3
+ size 550593184
checkpoint-1660/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoint-1660/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoint-1660/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-1660/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1ef3836a4e62c94ea88efcfc3a0f0220ab2afef0fa04c256e6bb2a3618adae96
3
+ size 1101419875
checkpoint-1660/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9119b5703d82024d0965c86a2ce1ab60bc0b22901cc2420a42e1b208ec43648d
3
+ size 14645
checkpoint-1660/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3e133f5ed12cc47cc34a85c3ba2128c75a743660d8bc3b6577ccf9397ff38b0d
3
+ size 1465
checkpoint-1660/special_tokens_map.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": "<|im_end|>"
25
+ }
checkpoint-1660/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3f9d93e80cff961819dcba7d892cf9656e086a0cf83cdbef23f10c1a493faa2
3
+ size 11422061
checkpoint-1660/tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 32768,
203
+ "pad_token": "<|im_end|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
checkpoint-1660/trainer_state.json ADDED
@@ -0,0 +1,668 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 4.0,
6
+ "eval_steps": 500,
7
+ "global_step": 1660,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.060350030175015085,
14
+ "grad_norm": 0.17640693485736847,
15
+ "learning_rate": 9.599999999999999e-05,
16
+ "loss": 1.7813,
17
+ "mean_token_accuracy": 0.6300852990150452,
18
+ "num_tokens": 156656.0,
19
+ "step": 25
20
+ },
21
+ {
22
+ "epoch": 0.12070006035003017,
23
+ "grad_norm": 0.24193964898586273,
24
+ "learning_rate": 0.00019599999999999997,
25
+ "loss": 0.9197,
26
+ "mean_token_accuracy": 0.768382026553154,
27
+ "num_tokens": 282982.0,
28
+ "step": 50
29
+ },
30
+ {
31
+ "epoch": 0.18105009052504525,
32
+ "grad_norm": 0.16499435901641846,
33
+ "learning_rate": 0.000296,
34
+ "loss": 0.5906,
35
+ "mean_token_accuracy": 0.8341364151239395,
36
+ "num_tokens": 441181.0,
37
+ "step": 75
38
+ },
39
+ {
40
+ "epoch": 0.24140012070006034,
41
+ "grad_norm": 0.23563049733638763,
42
+ "learning_rate": 0.0002999269005776963,
43
+ "loss": 0.4832,
44
+ "mean_token_accuracy": 0.8592967188358307,
45
+ "num_tokens": 567644.0,
46
+ "step": 100
47
+ },
48
+ {
49
+ "epoch": 0.30175015087507545,
50
+ "grad_norm": 0.22556591033935547,
51
+ "learning_rate": 0.0002996953705789175,
52
+ "loss": 0.3612,
53
+ "mean_token_accuracy": 0.8925437909364701,
54
+ "num_tokens": 725987.0,
55
+ "step": 125
56
+ },
57
+ {
58
+ "epoch": 0.3621001810500905,
59
+ "grad_norm": 0.33429527282714844,
60
+ "learning_rate": 0.00029930552794275785,
61
+ "loss": 0.3126,
62
+ "mean_token_accuracy": 0.9086851555109025,
63
+ "num_tokens": 853185.0,
64
+ "step": 150
65
+ },
66
+ {
67
+ "epoch": 0.4224502112251056,
68
+ "grad_norm": 0.27340370416641235,
69
+ "learning_rate": 0.0002987577849532824,
70
+ "loss": 0.2343,
71
+ "mean_token_accuracy": 0.9301495373249054,
72
+ "num_tokens": 1011232.0,
73
+ "step": 175
74
+ },
75
+ {
76
+ "epoch": 0.4828002414001207,
77
+ "grad_norm": 0.2711191475391388,
78
+ "learning_rate": 0.00029805272088449905,
79
+ "loss": 0.2021,
80
+ "mean_token_accuracy": 0.9406860828399658,
81
+ "num_tokens": 1138074.0,
82
+ "step": 200
83
+ },
84
+ {
85
+ "epoch": 0.5431502715751357,
86
+ "grad_norm": 0.19240038096904755,
87
+ "learning_rate": 0.00029719108138773827,
88
+ "loss": 0.1508,
89
+ "mean_token_accuracy": 0.9550948125123978,
90
+ "num_tokens": 1293601.0,
91
+ "step": 225
92
+ },
93
+ {
94
+ "epoch": 0.6035003017501509,
95
+ "grad_norm": 0.27221739292144775,
96
+ "learning_rate": 0.00029617377770307837,
97
+ "loss": 0.1563,
98
+ "mean_token_accuracy": 0.9542003554105759,
99
+ "num_tokens": 1418074.0,
100
+ "step": 250
101
+ },
102
+ {
103
+ "epoch": 0.663850331925166,
104
+ "grad_norm": 0.25977134704589844,
105
+ "learning_rate": 0.0002950018856956494,
106
+ "loss": 0.1228,
107
+ "mean_token_accuracy": 0.9640595990419388,
108
+ "num_tokens": 1577856.0,
109
+ "step": 275
110
+ },
111
+ {
112
+ "epoch": 0.724200362100181,
113
+ "grad_norm": 0.2311161458492279,
114
+ "learning_rate": 0.0002936766447178356,
115
+ "loss": 0.1229,
116
+ "mean_token_accuracy": 0.9646531140804291,
117
+ "num_tokens": 1704393.0,
118
+ "step": 300
119
+ },
120
+ {
121
+ "epoch": 0.7845503922751962,
122
+ "grad_norm": 0.1375264674425125,
123
+ "learning_rate": 0.0002921994562985788,
124
+ "loss": 0.0972,
125
+ "mean_token_accuracy": 0.9722524845600128,
126
+ "num_tokens": 1860935.0,
127
+ "step": 325
128
+ },
129
+ {
130
+ "epoch": 0.8449004224502112,
131
+ "grad_norm": 0.2860631048679352,
132
+ "learning_rate": 0.0002905718826611708,
133
+ "loss": 0.0853,
134
+ "mean_token_accuracy": 0.9756521546840667,
135
+ "num_tokens": 1988266.0,
136
+ "step": 350
137
+ },
138
+ {
139
+ "epoch": 0.9052504526252263,
140
+ "grad_norm": 0.11123040318489075,
141
+ "learning_rate": 0.00028879564507109946,
142
+ "loss": 0.0814,
143
+ "mean_token_accuracy": 0.9769123244285584,
144
+ "num_tokens": 2146122.0,
145
+ "step": 375
146
+ },
147
+ {
148
+ "epoch": 0.9656004828002414,
149
+ "grad_norm": 0.239139586687088,
150
+ "learning_rate": 0.0002868726220156981,
151
+ "loss": 0.0696,
152
+ "mean_token_accuracy": 0.9802538651227951,
153
+ "num_tokens": 2273996.0,
154
+ "step": 400
155
+ },
156
+ {
157
+ "epoch": 1.0,
158
+ "eval_loss": 0.07211296260356903,
159
+ "eval_mean_token_accuracy": 0.979879263285044,
160
+ "eval_num_tokens": 2354180.0,
161
+ "eval_runtime": 29.4819,
162
+ "eval_samples_per_second": 12.516,
163
+ "eval_steps_per_second": 6.275,
164
+ "step": 415
165
+ },
166
+ {
167
+ "epoch": 1.024140012070006,
168
+ "grad_norm": 0.13852086663246155,
169
+ "learning_rate": 0.0002848048472175225,
170
+ "loss": 0.0764,
171
+ "mean_token_accuracy": 0.9782544571099822,
172
+ "num_tokens": 2422077.0,
173
+ "step": 425
174
+ },
175
+ {
176
+ "epoch": 1.0844900422450212,
177
+ "grad_norm": 0.17753440141677856,
178
+ "learning_rate": 0.00028259450748355637,
179
+ "loss": 0.0527,
180
+ "mean_token_accuracy": 0.9847306323051452,
181
+ "num_tokens": 2564180.0,
182
+ "step": 450
183
+ },
184
+ {
185
+ "epoch": 1.1448400724200363,
186
+ "grad_norm": 0.13473442196846008,
187
+ "learning_rate": 0.00028024394039252005,
188
+ "loss": 0.0697,
189
+ "mean_token_accuracy": 0.9803690612316132,
190
+ "num_tokens": 2705737.0,
191
+ "step": 475
192
+ },
193
+ {
194
+ "epoch": 1.2051901025950513,
195
+ "grad_norm": 0.04998031258583069,
196
+ "learning_rate": 0.0002777556318227281,
197
+ "loss": 0.0452,
198
+ "mean_token_accuracy": 0.987179564833641,
199
+ "num_tokens": 2848782.0,
200
+ "step": 500
201
+ },
202
+ {
203
+ "epoch": 1.2655401327700664,
204
+ "grad_norm": 0.09412259608507156,
205
+ "learning_rate": 0.00027513221332311073,
206
+ "loss": 0.0615,
207
+ "mean_token_accuracy": 0.9825534737110138,
208
+ "num_tokens": 2991024.0,
209
+ "step": 525
210
+ },
211
+ {
212
+ "epoch": 1.3258901629450814,
213
+ "grad_norm": 0.12740211188793182,
214
+ "learning_rate": 0.0002723764593301788,
215
+ "loss": 0.0452,
216
+ "mean_token_accuracy": 0.9870287185907364,
217
+ "num_tokens": 3132622.0,
218
+ "step": 550
219
+ },
220
+ {
221
+ "epoch": 1.3862401931200965,
222
+ "grad_norm": 0.11777028441429138,
223
+ "learning_rate": 0.0002694912842338756,
224
+ "loss": 0.0568,
225
+ "mean_token_accuracy": 0.9838440799713135,
226
+ "num_tokens": 3273143.0,
227
+ "step": 575
228
+ },
229
+ {
230
+ "epoch": 1.4465902232951118,
231
+ "grad_norm": 0.09758122265338898,
232
+ "learning_rate": 0.0002664797392954194,
233
+ "loss": 0.0444,
234
+ "mean_token_accuracy": 0.986908946633339,
235
+ "num_tokens": 3416381.0,
236
+ "step": 600
237
+ },
238
+ {
239
+ "epoch": 1.5069402534701268,
240
+ "grad_norm": 0.0658789575099945,
241
+ "learning_rate": 0.0002633450094203953,
242
+ "loss": 0.0535,
243
+ "mean_token_accuracy": 0.9848115313053131,
244
+ "num_tokens": 3558249.0,
245
+ "step": 625
246
+ },
247
+ {
248
+ "epoch": 1.567290283645142,
249
+ "grad_norm": 0.07210762798786163,
250
+ "learning_rate": 0.000260090409790509,
251
+ "loss": 0.0409,
252
+ "mean_token_accuracy": 0.9878959685564042,
253
+ "num_tokens": 3700350.0,
254
+ "step": 650
255
+ },
256
+ {
257
+ "epoch": 1.627640313820157,
258
+ "grad_norm": 0.09006072580814362,
259
+ "learning_rate": 0.000256719382357566,
260
+ "loss": 0.052,
261
+ "mean_token_accuracy": 0.9852559435367584,
262
+ "num_tokens": 3842983.0,
263
+ "step": 675
264
+ },
265
+ {
266
+ "epoch": 1.687990343995172,
267
+ "grad_norm": 0.07121206820011139,
268
+ "learning_rate": 0.0002532354922033823,
269
+ "loss": 0.0401,
270
+ "mean_token_accuracy": 0.9882262688875199,
271
+ "num_tokens": 3985789.0,
272
+ "step": 700
273
+ },
274
+ {
275
+ "epoch": 1.748340374170187,
276
+ "grad_norm": 0.049150578677654266,
277
+ "learning_rate": 0.00024964242376947747,
278
+ "loss": 0.0514,
279
+ "mean_token_accuracy": 0.9852595126628876,
280
+ "num_tokens": 4128158.0,
281
+ "step": 725
282
+ },
283
+ {
284
+ "epoch": 1.8086904043452021,
285
+ "grad_norm": 0.08217272907495499,
286
+ "learning_rate": 0.000245943976960537,
287
+ "loss": 0.0373,
288
+ "mean_token_accuracy": 0.9887230151891708,
289
+ "num_tokens": 4270705.0,
290
+ "step": 750
291
+ },
292
+ {
293
+ "epoch": 1.8690404345202172,
294
+ "grad_norm": 0.060381677001714706,
295
+ "learning_rate": 0.00024214406312576472,
296
+ "loss": 0.051,
297
+ "mean_token_accuracy": 0.9850554609298706,
298
+ "num_tokens": 4412064.0,
299
+ "step": 775
300
+ },
301
+ {
302
+ "epoch": 1.9293904646952322,
303
+ "grad_norm": 0.07599000632762909,
304
+ "learning_rate": 0.00023824670092237557,
305
+ "loss": 0.0385,
306
+ "mean_token_accuracy": 0.9883499753475189,
307
+ "num_tokens": 4554646.0,
308
+ "step": 800
309
+ },
310
+ {
311
+ "epoch": 1.9897404948702473,
312
+ "grad_norm": 0.06878010928630829,
313
+ "learning_rate": 0.00023425601206560257,
314
+ "loss": 0.0432,
315
+ "mean_token_accuracy": 0.9873087042570114,
316
+ "num_tokens": 4688134.0,
317
+ "step": 825
318
+ },
319
+ {
320
+ "epoch": 2.0,
321
+ "eval_loss": 0.04542902857065201,
322
+ "eval_mean_token_accuracy": 0.9870176924241556,
323
+ "eval_num_tokens": 4708360.0,
324
+ "eval_runtime": 29.4629,
325
+ "eval_samples_per_second": 12.524,
326
+ "eval_steps_per_second": 6.279,
327
+ "step": 830
328
+ },
329
+ {
330
+ "epoch": 2.048280024140012,
331
+ "grad_norm": 0.07973352819681168,
332
+ "learning_rate": 0.00023017621696971407,
333
+ "loss": 0.0424,
334
+ "mean_token_accuracy": 0.9869058310371084,
335
+ "num_tokens": 4837256.0,
336
+ "step": 850
337
+ },
338
+ {
339
+ "epoch": 2.1086300543150274,
340
+ "grad_norm": 0.3017246723175049,
341
+ "learning_rate": 0.0002260116302846495,
342
+ "loss": 0.0294,
343
+ "mean_token_accuracy": 0.9908489334583283,
344
+ "num_tokens": 4969729.0,
345
+ "step": 875
346
+ },
347
+ {
348
+ "epoch": 2.1689800844900424,
349
+ "grad_norm": 0.05929604917764664,
350
+ "learning_rate": 0.0002217666563329952,
351
+ "loss": 0.0407,
352
+ "mean_token_accuracy": 0.9875844532251358,
353
+ "num_tokens": 5120477.0,
354
+ "step": 900
355
+ },
356
+ {
357
+ "epoch": 2.2293301146650575,
358
+ "grad_norm": 0.10643558949232101,
359
+ "learning_rate": 0.00021744578445212544,
360
+ "loss": 0.03,
361
+ "mean_token_accuracy": 0.9906252521276474,
362
+ "num_tokens": 5253578.0,
363
+ "step": 925
364
+ },
365
+ {
366
+ "epoch": 2.2896801448400725,
367
+ "grad_norm": 0.07998061180114746,
368
+ "learning_rate": 0.0002130535842464348,
369
+ "loss": 0.0405,
370
+ "mean_token_accuracy": 0.9873760217428207,
371
+ "num_tokens": 5406645.0,
372
+ "step": 950
373
+ },
374
+ {
375
+ "epoch": 2.3500301750150876,
376
+ "grad_norm": 0.03785248100757599,
377
+ "learning_rate": 0.0002085947007546829,
378
+ "loss": 0.0286,
379
+ "mean_token_accuracy": 0.9912718170881272,
380
+ "num_tokens": 5540521.0,
381
+ "step": 975
382
+ },
383
+ {
384
+ "epoch": 2.4103802051901027,
385
+ "grad_norm": 0.038521163165569305,
386
+ "learning_rate": 0.00020407384953756216,
387
+ "loss": 0.0402,
388
+ "mean_token_accuracy": 0.9876785135269165,
389
+ "num_tokens": 5691357.0,
390
+ "step": 1000
391
+ },
392
+ {
393
+ "epoch": 2.4707302353651177,
394
+ "grad_norm": 0.08188804239034653,
395
+ "learning_rate": 0.00019949581169068456,
396
+ "loss": 0.0286,
397
+ "mean_token_accuracy": 0.991096887588501,
398
+ "num_tokens": 5824399.0,
399
+ "step": 1025
400
+ },
401
+ {
402
+ "epoch": 2.5310802655401328,
403
+ "grad_norm": 0.07109837234020233,
404
+ "learning_rate": 0.0001948654287882601,
405
+ "loss": 0.0388,
406
+ "mean_token_accuracy": 0.9885295808315278,
407
+ "num_tokens": 5975841.0,
408
+ "step": 1050
409
+ },
410
+ {
411
+ "epoch": 2.591430295715148,
412
+ "grad_norm": 0.06275477260351181,
413
+ "learning_rate": 0.00019018759776281605,
414
+ "loss": 0.0261,
415
+ "mean_token_accuracy": 0.9916540479660034,
416
+ "num_tokens": 6108567.0,
417
+ "step": 1075
418
+ },
419
+ {
420
+ "epoch": 2.651780325890163,
421
+ "grad_norm": 0.04038365185260773,
422
+ "learning_rate": 0.00018546726572637065,
423
+ "loss": 0.0352,
424
+ "mean_token_accuracy": 0.9892910522222519,
425
+ "num_tokens": 6259991.0,
426
+ "step": 1100
427
+ },
428
+ {
429
+ "epoch": 2.712130356065178,
430
+ "grad_norm": 0.09150233864784241,
431
+ "learning_rate": 0.00018070942473853873,
432
+ "loss": 0.0255,
433
+ "mean_token_accuracy": 0.9921514791250229,
434
+ "num_tokens": 6393402.0,
435
+ "step": 1125
436
+ },
437
+ {
438
+ "epoch": 2.772480386240193,
439
+ "grad_norm": 0.04401474818587303,
440
+ "learning_rate": 0.00017591910652710262,
441
+ "loss": 0.0355,
442
+ "mean_token_accuracy": 0.9891881144046784,
443
+ "num_tokens": 6544386.0,
444
+ "step": 1150
445
+ },
446
+ {
447
+ "epoch": 2.832830416415208,
448
+ "grad_norm": 0.16860009729862213,
449
+ "learning_rate": 0.00017110137716663107,
450
+ "loss": 0.026,
451
+ "mean_token_accuracy": 0.9918778198957443,
452
+ "num_tokens": 6674740.0,
453
+ "step": 1175
454
+ },
455
+ {
456
+ "epoch": 2.8931804465902236,
457
+ "grad_norm": 0.05165860429406166,
458
+ "learning_rate": 0.0001662613317207742,
459
+ "loss": 0.0403,
460
+ "mean_token_accuracy": 0.9879327750205994,
461
+ "num_tokens": 6826652.0,
462
+ "step": 1200
463
+ },
464
+ {
465
+ "epoch": 2.9535304767652386,
466
+ "grad_norm": 0.06370134651660919,
467
+ "learning_rate": 0.00016140408885390107,
468
+ "loss": 0.0273,
469
+ "mean_token_accuracy": 0.9915495270490646,
470
+ "num_tokens": 6960481.0,
471
+ "step": 1225
472
+ },
473
+ {
474
+ "epoch": 3.0,
475
+ "eval_loss": 0.038739174604415894,
476
+ "eval_mean_token_accuracy": 0.9888446437345969,
477
+ "eval_num_tokens": 7062540.0,
478
+ "eval_runtime": 29.4618,
479
+ "eval_samples_per_second": 12.525,
480
+ "eval_steps_per_second": 6.279,
481
+ "step": 1245
482
+ },
483
+ {
484
+ "epoch": 3.012070006035003,
485
+ "grad_norm": 0.05011030286550522,
486
+ "learning_rate": 0.0001565347854177771,
487
+ "loss": 0.0303,
488
+ "mean_token_accuracy": 0.9901853019429236,
489
+ "num_tokens": 7098331.0,
490
+ "step": 1250
491
+ },
492
+ {
493
+ "epoch": 3.0724200362100182,
494
+ "grad_norm": 0.05125705525279045,
495
+ "learning_rate": 0.00015165857101900816,
496
+ "loss": 0.0233,
497
+ "mean_token_accuracy": 0.9924298238754272,
498
+ "num_tokens": 7246298.0,
499
+ "step": 1275
500
+ },
501
+ {
502
+ "epoch": 3.1327700663850333,
503
+ "grad_norm": 0.059397757053375244,
504
+ "learning_rate": 0.00014678060257299454,
505
+ "loss": 0.027,
506
+ "mean_token_accuracy": 0.991271983385086,
507
+ "num_tokens": 7381191.0,
508
+ "step": 1300
509
+ },
510
+ {
511
+ "epoch": 3.1931200965600484,
512
+ "grad_norm": 0.031168634071946144,
513
+ "learning_rate": 0.00014190603885015624,
514
+ "loss": 0.025,
515
+ "mean_token_accuracy": 0.9918223685026168,
516
+ "num_tokens": 7529646.0,
517
+ "step": 1325
518
+ },
519
+ {
520
+ "epoch": 3.2534701267350634,
521
+ "grad_norm": 0.06622699648141861,
522
+ "learning_rate": 0.00013704003502019595,
523
+ "loss": 0.0274,
524
+ "mean_token_accuracy": 0.9909968906641007,
525
+ "num_tokens": 7665384.0,
526
+ "step": 1350
527
+ },
528
+ {
529
+ "epoch": 3.3138201569100785,
530
+ "grad_norm": 0.040858324617147446,
531
+ "learning_rate": 0.0001321877372001702,
532
+ "loss": 0.0234,
533
+ "mean_token_accuracy": 0.992581251859665,
534
+ "num_tokens": 7814867.0,
535
+ "step": 1375
536
+ },
537
+ {
538
+ "epoch": 3.3741701870850935,
539
+ "grad_norm": 0.06217949092388153,
540
+ "learning_rate": 0.00012735427701213444,
541
+ "loss": 0.0264,
542
+ "mean_token_accuracy": 0.9915199714899063,
543
+ "num_tokens": 7951694.0,
544
+ "step": 1400
545
+ },
546
+ {
547
+ "epoch": 3.4345202172601086,
548
+ "grad_norm": 0.044205911457538605,
549
+ "learning_rate": 0.00012254476615611694,
550
+ "loss": 0.0229,
551
+ "mean_token_accuracy": 0.9923870205879212,
552
+ "num_tokens": 8099509.0,
553
+ "step": 1425
554
+ },
555
+ {
556
+ "epoch": 3.4948702474351236,
557
+ "grad_norm": 0.042222440242767334,
558
+ "learning_rate": 0.00011776429100416252,
559
+ "loss": 0.0283,
560
+ "mean_token_accuracy": 0.9907158309221268,
561
+ "num_tokens": 8235602.0,
562
+ "step": 1450
563
+ },
564
+ {
565
+ "epoch": 3.5552202776101387,
566
+ "grad_norm": 0.036372531205415726,
567
+ "learning_rate": 0.00011301790722116113,
568
+ "loss": 0.0227,
569
+ "mean_token_accuracy": 0.9924897265434265,
570
+ "num_tokens": 8384445.0,
571
+ "step": 1475
572
+ },
573
+ {
574
+ "epoch": 3.6155703077851538,
575
+ "grad_norm": 0.06498222798109055,
576
+ "learning_rate": 0.00010831063441815225,
577
+ "loss": 0.0254,
578
+ "mean_token_accuracy": 0.9921332412958145,
579
+ "num_tokens": 8520372.0,
580
+ "step": 1500
581
+ },
582
+ {
583
+ "epoch": 3.675920337960169,
584
+ "grad_norm": 0.03929189220070839,
585
+ "learning_rate": 0.0001036474508437579,
586
+ "loss": 0.0221,
587
+ "mean_token_accuracy": 0.9927822852134705,
588
+ "num_tokens": 8668318.0,
589
+ "step": 1525
590
+ },
591
+ {
592
+ "epoch": 3.736270368135184,
593
+ "grad_norm": 0.06582839041948318,
594
+ "learning_rate": 9.903328811935959e-05,
595
+ "loss": 0.0245,
596
+ "mean_token_accuracy": 0.9920618611574173,
597
+ "num_tokens": 8805749.0,
598
+ "step": 1550
599
+ },
600
+ {
601
+ "epoch": 3.796620398310199,
602
+ "grad_norm": 0.04050470143556595,
603
+ "learning_rate": 9.447302602358619e-05,
604
+ "loss": 0.0219,
605
+ "mean_token_accuracy": 0.9927525413036347,
606
+ "num_tokens": 8953240.0,
607
+ "step": 1575
608
+ },
609
+ {
610
+ "epoch": 3.856970428485214,
611
+ "grad_norm": 0.06876744329929352,
612
+ "learning_rate": 8.997148733162942e-05,
613
+ "loss": 0.0263,
614
+ "mean_token_accuracy": 0.991570799946785,
615
+ "num_tokens": 9088072.0,
616
+ "step": 1600
617
+ },
618
+ {
619
+ "epoch": 3.9173204586602295,
620
+ "grad_norm": 0.026705719530582428,
621
+ "learning_rate": 8.553343271484368e-05,
622
+ "loss": 0.0226,
623
+ "mean_token_accuracy": 0.9928545600175858,
624
+ "num_tokens": 9236720.0,
625
+ "step": 1625
626
+ },
627
+ {
628
+ "epoch": 3.9776704888352445,
629
+ "grad_norm": 0.03888670355081558,
630
+ "learning_rate": 8.116355570602482e-05,
631
+ "loss": 0.0228,
632
+ "mean_token_accuracy": 0.9928395706415176,
633
+ "num_tokens": 9369354.0,
634
+ "step": 1650
635
+ },
636
+ {
637
+ "epoch": 4.0,
638
+ "eval_loss": 0.03669499605894089,
639
+ "eval_mean_token_accuracy": 0.9898246610486829,
640
+ "eval_num_tokens": 9416720.0,
641
+ "eval_runtime": 29.4478,
642
+ "eval_samples_per_second": 12.531,
643
+ "eval_steps_per_second": 6.282,
644
+ "step": 1660
645
+ }
646
+ ],
647
+ "logging_steps": 25,
648
+ "max_steps": 2490,
649
+ "num_input_tokens_seen": 0,
650
+ "num_train_epochs": 6,
651
+ "save_steps": 500,
652
+ "stateful_callbacks": {
653
+ "TrainerControl": {
654
+ "args": {
655
+ "should_epoch_stop": false,
656
+ "should_evaluate": false,
657
+ "should_log": false,
658
+ "should_save": true,
659
+ "should_training_stop": false
660
+ },
661
+ "attributes": {}
662
+ }
663
+ },
664
+ "total_flos": 7.992703903390188e+17,
665
+ "train_batch_size": 2,
666
+ "trial_name": null,
667
+ "trial_params": null
668
+ }
checkpoint-1660/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a46b0daa7fdfc376322a8afaffd8c2c7c13f904fdcef5c58858545c671ae355b
3
+ size 5969
checkpoint-1660/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2075/README.md ADDED
@@ -0,0 +1,209 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-Coder-14B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ ---
12
+
13
+ # Model Card for Model ID
14
+
15
+ <!-- Provide a quick summary of what the model is/does. -->
16
+
17
+
18
+
19
+ ## Model Details
20
+
21
+ ### Model Description
22
+
23
+ <!-- Provide a longer summary of what this model is. -->
24
+
25
+
26
+
27
+ - **Developed by:** [More Information Needed]
28
+ - **Funded by [optional]:** [More Information Needed]
29
+ - **Shared by [optional]:** [More Information Needed]
30
+ - **Model type:** [More Information Needed]
31
+ - **Language(s) (NLP):** [More Information Needed]
32
+ - **License:** [More Information Needed]
33
+ - **Finetuned from model [optional]:** [More Information Needed]
34
+
35
+ ### Model Sources [optional]
36
+
37
+ <!-- Provide the basic links for the model. -->
38
+
39
+ - **Repository:** [More Information Needed]
40
+ - **Paper [optional]:** [More Information Needed]
41
+ - **Demo [optional]:** [More Information Needed]
42
+
43
+ ## Uses
44
+
45
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
46
+
47
+ ### Direct Use
48
+
49
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
50
+
51
+ [More Information Needed]
52
+
53
+ ### Downstream Use [optional]
54
+
55
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
56
+
57
+ [More Information Needed]
58
+
59
+ ### Out-of-Scope Use
60
+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
62
+
63
+ [More Information Needed]
64
+
65
+ ## Bias, Risks, and Limitations
66
+
67
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
68
+
69
+ [More Information Needed]
70
+
71
+ ### Recommendations
72
+
73
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
74
+
75
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
76
+
77
+ ## How to Get Started with the Model
78
+
79
+ Use the code below to get started with the model.
80
+
81
+ [More Information Needed]
82
+
83
+ ## Training Details
84
+
85
+ ### Training Data
86
+
87
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
88
+
89
+ [More Information Needed]
90
+
91
+ ### Training Procedure
92
+
93
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
94
+
95
+ #### Preprocessing [optional]
96
+
97
+ [More Information Needed]
98
+
99
+
100
+ #### Training Hyperparameters
101
+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
103
+
104
+ #### Speeds, Sizes, Times [optional]
105
+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
107
+
108
+ [More Information Needed]
109
+
110
+ ## Evaluation
111
+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
113
+
114
+ ### Testing Data, Factors & Metrics
115
+
116
+ #### Testing Data
117
+
118
+ <!-- This should link to a Dataset Card if possible. -->
119
+
120
+ [More Information Needed]
121
+
122
+ #### Factors
123
+
124
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
125
+
126
+ [More Information Needed]
127
+
128
+ #### Metrics
129
+
130
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
131
+
132
+ [More Information Needed]
133
+
134
+ ### Results
135
+
136
+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
141
+
142
+ ## Model Examination [optional]
143
+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
153
+
154
+ - **Hardware Type:** [More Information Needed]
155
+ - **Hours used:** [More Information Needed]
156
+ - **Cloud Provider:** [More Information Needed]
157
+ - **Compute Region:** [More Information Needed]
158
+ - **Carbon Emitted:** [More Information Needed]
159
+
160
+ ## Technical Specifications [optional]
161
+
162
+ ### Model Architecture and Objective
163
+
164
+ [More Information Needed]
165
+
166
+ ### Compute Infrastructure
167
+
168
+ [More Information Needed]
169
+
170
+ #### Hardware
171
+
172
+ [More Information Needed]
173
+
174
+ #### Software
175
+
176
+ [More Information Needed]
177
+
178
+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
181
+
182
+ **BibTeX:**
183
+
184
+ [More Information Needed]
185
+
186
+ **APA:**
187
+
188
+ [More Information Needed]
189
+
190
+ ## Glossary [optional]
191
+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
193
+
194
+ [More Information Needed]
195
+
196
+ ## More Information [optional]
197
+
198
+ [More Information Needed]
199
+
200
+ ## Model Card Authors [optional]
201
+
202
+ [More Information Needed]
203
+
204
+ ## Model Card Contact
205
+
206
+ [More Information Needed]
207
+ ### Framework versions
208
+
209
+ - PEFT 0.17.0
checkpoint-2075/adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "Qwen/Qwen2.5-Coder-14B-Instruct",
5
+ "bias": "none",
6
+ "corda_config": null,
7
+ "eva_config": null,
8
+ "exclude_modules": null,
9
+ "fan_in_fan_out": false,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 16,
17
+ "lora_bias": false,
18
+ "lora_dropout": 0.1,
19
+ "megatron_config": null,
20
+ "megatron_core": "megatron.core",
21
+ "modules_to_save": null,
22
+ "peft_type": "LORA",
23
+ "qalora_group_size": 16,
24
+ "r": 32,
25
+ "rank_pattern": {},
26
+ "revision": null,
27
+ "target_modules": [
28
+ "v_proj",
29
+ "up_proj",
30
+ "k_proj",
31
+ "gate_proj",
32
+ "down_proj",
33
+ "q_proj",
34
+ "o_proj"
35
+ ],
36
+ "target_parameters": null,
37
+ "task_type": "CAUSAL_LM",
38
+ "trainable_token_indices": null,
39
+ "use_dora": false,
40
+ "use_qalora": false,
41
+ "use_rslora": false
42
+ }
checkpoint-2075/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:19d52e11adeba688d0b3e00b209f3d02b7434d757f4897f592b7977f8ad00a0d
3
+ size 550593184
checkpoint-2075/added_tokens.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|box_end|>": 151649,
5
+ "<|box_start|>": 151648,
6
+ "<|endoftext|>": 151643,
7
+ "<|file_sep|>": 151664,
8
+ "<|fim_middle|>": 151660,
9
+ "<|fim_pad|>": 151662,
10
+ "<|fim_prefix|>": 151659,
11
+ "<|fim_suffix|>": 151661,
12
+ "<|im_end|>": 151645,
13
+ "<|im_start|>": 151644,
14
+ "<|image_pad|>": 151655,
15
+ "<|object_ref_end|>": 151647,
16
+ "<|object_ref_start|>": 151646,
17
+ "<|quad_end|>": 151651,
18
+ "<|quad_start|>": 151650,
19
+ "<|repo_name|>": 151663,
20
+ "<|video_pad|>": 151656,
21
+ "<|vision_end|>": 151653,
22
+ "<|vision_pad|>": 151654,
23
+ "<|vision_start|>": 151652
24
+ }
checkpoint-2075/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoint-2075/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-2075/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:189d8b1249c897b48c4037adc820c7302ea28a4e2bd3490e51eec3245b6f0512
3
+ size 1101419875
checkpoint-2075/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4bf96f323b0ed38974ec212078800042c002751a0caf0584859d3fa6eb4ef155
3
+ size 14645
checkpoint-2075/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c062568899dd95b92441d393d677366b1d66daac8abfc6912b15dc0b2426e01d
3
+ size 1465
checkpoint-2075/special_tokens_map.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": "<|im_end|>"
25
+ }
checkpoint-2075/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3f9d93e80cff961819dcba7d892cf9656e086a0cf83cdbef23f10c1a493faa2
3
+ size 11422061
checkpoint-2075/tokenizer_config.json ADDED
@@ -0,0 +1,207 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ }
181
+ },
182
+ "additional_special_tokens": [
183
+ "<|im_start|>",
184
+ "<|im_end|>",
185
+ "<|object_ref_start|>",
186
+ "<|object_ref_end|>",
187
+ "<|box_start|>",
188
+ "<|box_end|>",
189
+ "<|quad_start|>",
190
+ "<|quad_end|>",
191
+ "<|vision_start|>",
192
+ "<|vision_end|>",
193
+ "<|vision_pad|>",
194
+ "<|image_pad|>",
195
+ "<|video_pad|>"
196
+ ],
197
+ "bos_token": null,
198
+ "clean_up_tokenization_spaces": false,
199
+ "eos_token": "<|im_end|>",
200
+ "errors": "replace",
201
+ "extra_special_tokens": {},
202
+ "model_max_length": 32768,
203
+ "pad_token": "<|im_end|>",
204
+ "split_special_tokens": false,
205
+ "tokenizer_class": "Qwen2Tokenizer",
206
+ "unk_token": null
207
+ }
checkpoint-2075/trainer_state.json ADDED
@@ -0,0 +1,831 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 5.0,
6
+ "eval_steps": 500,
7
+ "global_step": 2075,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.060350030175015085,
14
+ "grad_norm": 0.17640693485736847,
15
+ "learning_rate": 9.599999999999999e-05,
16
+ "loss": 1.7813,
17
+ "mean_token_accuracy": 0.6300852990150452,
18
+ "num_tokens": 156656.0,
19
+ "step": 25
20
+ },
21
+ {
22
+ "epoch": 0.12070006035003017,
23
+ "grad_norm": 0.24193964898586273,
24
+ "learning_rate": 0.00019599999999999997,
25
+ "loss": 0.9197,
26
+ "mean_token_accuracy": 0.768382026553154,
27
+ "num_tokens": 282982.0,
28
+ "step": 50
29
+ },
30
+ {
31
+ "epoch": 0.18105009052504525,
32
+ "grad_norm": 0.16499435901641846,
33
+ "learning_rate": 0.000296,
34
+ "loss": 0.5906,
35
+ "mean_token_accuracy": 0.8341364151239395,
36
+ "num_tokens": 441181.0,
37
+ "step": 75
38
+ },
39
+ {
40
+ "epoch": 0.24140012070006034,
41
+ "grad_norm": 0.23563049733638763,
42
+ "learning_rate": 0.0002999269005776963,
43
+ "loss": 0.4832,
44
+ "mean_token_accuracy": 0.8592967188358307,
45
+ "num_tokens": 567644.0,
46
+ "step": 100
47
+ },
48
+ {
49
+ "epoch": 0.30175015087507545,
50
+ "grad_norm": 0.22556591033935547,
51
+ "learning_rate": 0.0002996953705789175,
52
+ "loss": 0.3612,
53
+ "mean_token_accuracy": 0.8925437909364701,
54
+ "num_tokens": 725987.0,
55
+ "step": 125
56
+ },
57
+ {
58
+ "epoch": 0.3621001810500905,
59
+ "grad_norm": 0.33429527282714844,
60
+ "learning_rate": 0.00029930552794275785,
61
+ "loss": 0.3126,
62
+ "mean_token_accuracy": 0.9086851555109025,
63
+ "num_tokens": 853185.0,
64
+ "step": 150
65
+ },
66
+ {
67
+ "epoch": 0.4224502112251056,
68
+ "grad_norm": 0.27340370416641235,
69
+ "learning_rate": 0.0002987577849532824,
70
+ "loss": 0.2343,
71
+ "mean_token_accuracy": 0.9301495373249054,
72
+ "num_tokens": 1011232.0,
73
+ "step": 175
74
+ },
75
+ {
76
+ "epoch": 0.4828002414001207,
77
+ "grad_norm": 0.2711191475391388,
78
+ "learning_rate": 0.00029805272088449905,
79
+ "loss": 0.2021,
80
+ "mean_token_accuracy": 0.9406860828399658,
81
+ "num_tokens": 1138074.0,
82
+ "step": 200
83
+ },
84
+ {
85
+ "epoch": 0.5431502715751357,
86
+ "grad_norm": 0.19240038096904755,
87
+ "learning_rate": 0.00029719108138773827,
88
+ "loss": 0.1508,
89
+ "mean_token_accuracy": 0.9550948125123978,
90
+ "num_tokens": 1293601.0,
91
+ "step": 225
92
+ },
93
+ {
94
+ "epoch": 0.6035003017501509,
95
+ "grad_norm": 0.27221739292144775,
96
+ "learning_rate": 0.00029617377770307837,
97
+ "loss": 0.1563,
98
+ "mean_token_accuracy": 0.9542003554105759,
99
+ "num_tokens": 1418074.0,
100
+ "step": 250
101
+ },
102
+ {
103
+ "epoch": 0.663850331925166,
104
+ "grad_norm": 0.25977134704589844,
105
+ "learning_rate": 0.0002950018856956494,
106
+ "loss": 0.1228,
107
+ "mean_token_accuracy": 0.9640595990419388,
108
+ "num_tokens": 1577856.0,
109
+ "step": 275
110
+ },
111
+ {
112
+ "epoch": 0.724200362100181,
113
+ "grad_norm": 0.2311161458492279,
114
+ "learning_rate": 0.0002936766447178356,
115
+ "loss": 0.1229,
116
+ "mean_token_accuracy": 0.9646531140804291,
117
+ "num_tokens": 1704393.0,
118
+ "step": 300
119
+ },
120
+ {
121
+ "epoch": 0.7845503922751962,
122
+ "grad_norm": 0.1375264674425125,
123
+ "learning_rate": 0.0002921994562985788,
124
+ "loss": 0.0972,
125
+ "mean_token_accuracy": 0.9722524845600128,
126
+ "num_tokens": 1860935.0,
127
+ "step": 325
128
+ },
129
+ {
130
+ "epoch": 0.8449004224502112,
131
+ "grad_norm": 0.2860631048679352,
132
+ "learning_rate": 0.0002905718826611708,
133
+ "loss": 0.0853,
134
+ "mean_token_accuracy": 0.9756521546840667,
135
+ "num_tokens": 1988266.0,
136
+ "step": 350
137
+ },
138
+ {
139
+ "epoch": 0.9052504526252263,
140
+ "grad_norm": 0.11123040318489075,
141
+ "learning_rate": 0.00028879564507109946,
142
+ "loss": 0.0814,
143
+ "mean_token_accuracy": 0.9769123244285584,
144
+ "num_tokens": 2146122.0,
145
+ "step": 375
146
+ },
147
+ {
148
+ "epoch": 0.9656004828002414,
149
+ "grad_norm": 0.239139586687088,
150
+ "learning_rate": 0.0002868726220156981,
151
+ "loss": 0.0696,
152
+ "mean_token_accuracy": 0.9802538651227951,
153
+ "num_tokens": 2273996.0,
154
+ "step": 400
155
+ },
156
+ {
157
+ "epoch": 1.0,
158
+ "eval_loss": 0.07211296260356903,
159
+ "eval_mean_token_accuracy": 0.979879263285044,
160
+ "eval_num_tokens": 2354180.0,
161
+ "eval_runtime": 29.4819,
162
+ "eval_samples_per_second": 12.516,
163
+ "eval_steps_per_second": 6.275,
164
+ "step": 415
165
+ },
166
+ {
167
+ "epoch": 1.024140012070006,
168
+ "grad_norm": 0.13852086663246155,
169
+ "learning_rate": 0.0002848048472175225,
170
+ "loss": 0.0764,
171
+ "mean_token_accuracy": 0.9782544571099822,
172
+ "num_tokens": 2422077.0,
173
+ "step": 425
174
+ },
175
+ {
176
+ "epoch": 1.0844900422450212,
177
+ "grad_norm": 0.17753440141677856,
178
+ "learning_rate": 0.00028259450748355637,
179
+ "loss": 0.0527,
180
+ "mean_token_accuracy": 0.9847306323051452,
181
+ "num_tokens": 2564180.0,
182
+ "step": 450
183
+ },
184
+ {
185
+ "epoch": 1.1448400724200363,
186
+ "grad_norm": 0.13473442196846008,
187
+ "learning_rate": 0.00028024394039252005,
188
+ "loss": 0.0697,
189
+ "mean_token_accuracy": 0.9803690612316132,
190
+ "num_tokens": 2705737.0,
191
+ "step": 475
192
+ },
193
+ {
194
+ "epoch": 1.2051901025950513,
195
+ "grad_norm": 0.04998031258583069,
196
+ "learning_rate": 0.0002777556318227281,
197
+ "loss": 0.0452,
198
+ "mean_token_accuracy": 0.987179564833641,
199
+ "num_tokens": 2848782.0,
200
+ "step": 500
201
+ },
202
+ {
203
+ "epoch": 1.2655401327700664,
204
+ "grad_norm": 0.09412259608507156,
205
+ "learning_rate": 0.00027513221332311073,
206
+ "loss": 0.0615,
207
+ "mean_token_accuracy": 0.9825534737110138,
208
+ "num_tokens": 2991024.0,
209
+ "step": 525
210
+ },
211
+ {
212
+ "epoch": 1.3258901629450814,
213
+ "grad_norm": 0.12740211188793182,
214
+ "learning_rate": 0.0002723764593301788,
215
+ "loss": 0.0452,
216
+ "mean_token_accuracy": 0.9870287185907364,
217
+ "num_tokens": 3132622.0,
218
+ "step": 550
219
+ },
220
+ {
221
+ "epoch": 1.3862401931200965,
222
+ "grad_norm": 0.11777028441429138,
223
+ "learning_rate": 0.0002694912842338756,
224
+ "loss": 0.0568,
225
+ "mean_token_accuracy": 0.9838440799713135,
226
+ "num_tokens": 3273143.0,
227
+ "step": 575
228
+ },
229
+ {
230
+ "epoch": 1.4465902232951118,
231
+ "grad_norm": 0.09758122265338898,
232
+ "learning_rate": 0.0002664797392954194,
233
+ "loss": 0.0444,
234
+ "mean_token_accuracy": 0.986908946633339,
235
+ "num_tokens": 3416381.0,
236
+ "step": 600
237
+ },
238
+ {
239
+ "epoch": 1.5069402534701268,
240
+ "grad_norm": 0.0658789575099945,
241
+ "learning_rate": 0.0002633450094203953,
242
+ "loss": 0.0535,
243
+ "mean_token_accuracy": 0.9848115313053131,
244
+ "num_tokens": 3558249.0,
245
+ "step": 625
246
+ },
247
+ {
248
+ "epoch": 1.567290283645142,
249
+ "grad_norm": 0.07210762798786163,
250
+ "learning_rate": 0.000260090409790509,
251
+ "loss": 0.0409,
252
+ "mean_token_accuracy": 0.9878959685564042,
253
+ "num_tokens": 3700350.0,
254
+ "step": 650
255
+ },
256
+ {
257
+ "epoch": 1.627640313820157,
258
+ "grad_norm": 0.09006072580814362,
259
+ "learning_rate": 0.000256719382357566,
260
+ "loss": 0.052,
261
+ "mean_token_accuracy": 0.9852559435367584,
262
+ "num_tokens": 3842983.0,
263
+ "step": 675
264
+ },
265
+ {
266
+ "epoch": 1.687990343995172,
267
+ "grad_norm": 0.07121206820011139,
268
+ "learning_rate": 0.0002532354922033823,
269
+ "loss": 0.0401,
270
+ "mean_token_accuracy": 0.9882262688875199,
271
+ "num_tokens": 3985789.0,
272
+ "step": 700
273
+ },
274
+ {
275
+ "epoch": 1.748340374170187,
276
+ "grad_norm": 0.049150578677654266,
277
+ "learning_rate": 0.00024964242376947747,
278
+ "loss": 0.0514,
279
+ "mean_token_accuracy": 0.9852595126628876,
280
+ "num_tokens": 4128158.0,
281
+ "step": 725
282
+ },
283
+ {
284
+ "epoch": 1.8086904043452021,
285
+ "grad_norm": 0.08217272907495499,
286
+ "learning_rate": 0.000245943976960537,
287
+ "loss": 0.0373,
288
+ "mean_token_accuracy": 0.9887230151891708,
289
+ "num_tokens": 4270705.0,
290
+ "step": 750
291
+ },
292
+ {
293
+ "epoch": 1.8690404345202172,
294
+ "grad_norm": 0.060381677001714706,
295
+ "learning_rate": 0.00024214406312576472,
296
+ "loss": 0.051,
297
+ "mean_token_accuracy": 0.9850554609298706,
298
+ "num_tokens": 4412064.0,
299
+ "step": 775
300
+ },
301
+ {
302
+ "epoch": 1.9293904646952322,
303
+ "grad_norm": 0.07599000632762909,
304
+ "learning_rate": 0.00023824670092237557,
305
+ "loss": 0.0385,
306
+ "mean_token_accuracy": 0.9883499753475189,
307
+ "num_tokens": 4554646.0,
308
+ "step": 800
309
+ },
310
+ {
311
+ "epoch": 1.9897404948702473,
312
+ "grad_norm": 0.06878010928630829,
313
+ "learning_rate": 0.00023425601206560257,
314
+ "loss": 0.0432,
315
+ "mean_token_accuracy": 0.9873087042570114,
316
+ "num_tokens": 4688134.0,
317
+ "step": 825
318
+ },
319
+ {
320
+ "epoch": 2.0,
321
+ "eval_loss": 0.04542902857065201,
322
+ "eval_mean_token_accuracy": 0.9870176924241556,
323
+ "eval_num_tokens": 4708360.0,
324
+ "eval_runtime": 29.4629,
325
+ "eval_samples_per_second": 12.524,
326
+ "eval_steps_per_second": 6.279,
327
+ "step": 830
328
+ },
329
+ {
330
+ "epoch": 2.048280024140012,
331
+ "grad_norm": 0.07973352819681168,
332
+ "learning_rate": 0.00023017621696971407,
333
+ "loss": 0.0424,
334
+ "mean_token_accuracy": 0.9869058310371084,
335
+ "num_tokens": 4837256.0,
336
+ "step": 850
337
+ },
338
+ {
339
+ "epoch": 2.1086300543150274,
340
+ "grad_norm": 0.3017246723175049,
341
+ "learning_rate": 0.0002260116302846495,
342
+ "loss": 0.0294,
343
+ "mean_token_accuracy": 0.9908489334583283,
344
+ "num_tokens": 4969729.0,
345
+ "step": 875
346
+ },
347
+ {
348
+ "epoch": 2.1689800844900424,
349
+ "grad_norm": 0.05929604917764664,
350
+ "learning_rate": 0.0002217666563329952,
351
+ "loss": 0.0407,
352
+ "mean_token_accuracy": 0.9875844532251358,
353
+ "num_tokens": 5120477.0,
354
+ "step": 900
355
+ },
356
+ {
357
+ "epoch": 2.2293301146650575,
358
+ "grad_norm": 0.10643558949232101,
359
+ "learning_rate": 0.00021744578445212544,
360
+ "loss": 0.03,
361
+ "mean_token_accuracy": 0.9906252521276474,
362
+ "num_tokens": 5253578.0,
363
+ "step": 925
364
+ },
365
+ {
366
+ "epoch": 2.2896801448400725,
367
+ "grad_norm": 0.07998061180114746,
368
+ "learning_rate": 0.0002130535842464348,
369
+ "loss": 0.0405,
370
+ "mean_token_accuracy": 0.9873760217428207,
371
+ "num_tokens": 5406645.0,
372
+ "step": 950
373
+ },
374
+ {
375
+ "epoch": 2.3500301750150876,
376
+ "grad_norm": 0.03785248100757599,
377
+ "learning_rate": 0.0002085947007546829,
378
+ "loss": 0.0286,
379
+ "mean_token_accuracy": 0.9912718170881272,
380
+ "num_tokens": 5540521.0,
381
+ "step": 975
382
+ },
383
+ {
384
+ "epoch": 2.4103802051901027,
385
+ "grad_norm": 0.038521163165569305,
386
+ "learning_rate": 0.00020407384953756216,
387
+ "loss": 0.0402,
388
+ "mean_token_accuracy": 0.9876785135269165,
389
+ "num_tokens": 5691357.0,
390
+ "step": 1000
391
+ },
392
+ {
393
+ "epoch": 2.4707302353651177,
394
+ "grad_norm": 0.08188804239034653,
395
+ "learning_rate": 0.00019949581169068456,
396
+ "loss": 0.0286,
397
+ "mean_token_accuracy": 0.991096887588501,
398
+ "num_tokens": 5824399.0,
399
+ "step": 1025
400
+ },
401
+ {
402
+ "epoch": 2.5310802655401328,
403
+ "grad_norm": 0.07109837234020233,
404
+ "learning_rate": 0.0001948654287882601,
405
+ "loss": 0.0388,
406
+ "mean_token_accuracy": 0.9885295808315278,
407
+ "num_tokens": 5975841.0,
408
+ "step": 1050
409
+ },
410
+ {
411
+ "epoch": 2.591430295715148,
412
+ "grad_norm": 0.06275477260351181,
413
+ "learning_rate": 0.00019018759776281605,
414
+ "loss": 0.0261,
415
+ "mean_token_accuracy": 0.9916540479660034,
416
+ "num_tokens": 6108567.0,
417
+ "step": 1075
418
+ },
419
+ {
420
+ "epoch": 2.651780325890163,
421
+ "grad_norm": 0.04038365185260773,
422
+ "learning_rate": 0.00018546726572637065,
423
+ "loss": 0.0352,
424
+ "mean_token_accuracy": 0.9892910522222519,
425
+ "num_tokens": 6259991.0,
426
+ "step": 1100
427
+ },
428
+ {
429
+ "epoch": 2.712130356065178,
430
+ "grad_norm": 0.09150233864784241,
431
+ "learning_rate": 0.00018070942473853873,
432
+ "loss": 0.0255,
433
+ "mean_token_accuracy": 0.9921514791250229,
434
+ "num_tokens": 6393402.0,
435
+ "step": 1125
436
+ },
437
+ {
438
+ "epoch": 2.772480386240193,
439
+ "grad_norm": 0.04401474818587303,
440
+ "learning_rate": 0.00017591910652710262,
441
+ "loss": 0.0355,
442
+ "mean_token_accuracy": 0.9891881144046784,
443
+ "num_tokens": 6544386.0,
444
+ "step": 1150
445
+ },
446
+ {
447
+ "epoch": 2.832830416415208,
448
+ "grad_norm": 0.16860009729862213,
449
+ "learning_rate": 0.00017110137716663107,
450
+ "loss": 0.026,
451
+ "mean_token_accuracy": 0.9918778198957443,
452
+ "num_tokens": 6674740.0,
453
+ "step": 1175
454
+ },
455
+ {
456
+ "epoch": 2.8931804465902236,
457
+ "grad_norm": 0.05165860429406166,
458
+ "learning_rate": 0.0001662613317207742,
459
+ "loss": 0.0403,
460
+ "mean_token_accuracy": 0.9879327750205994,
461
+ "num_tokens": 6826652.0,
462
+ "step": 1200
463
+ },
464
+ {
465
+ "epoch": 2.9535304767652386,
466
+ "grad_norm": 0.06370134651660919,
467
+ "learning_rate": 0.00016140408885390107,
468
+ "loss": 0.0273,
469
+ "mean_token_accuracy": 0.9915495270490646,
470
+ "num_tokens": 6960481.0,
471
+ "step": 1225
472
+ },
473
+ {
474
+ "epoch": 3.0,
475
+ "eval_loss": 0.038739174604415894,
476
+ "eval_mean_token_accuracy": 0.9888446437345969,
477
+ "eval_num_tokens": 7062540.0,
478
+ "eval_runtime": 29.4618,
479
+ "eval_samples_per_second": 12.525,
480
+ "eval_steps_per_second": 6.279,
481
+ "step": 1245
482
+ },
483
+ {
484
+ "epoch": 3.012070006035003,
485
+ "grad_norm": 0.05011030286550522,
486
+ "learning_rate": 0.0001565347854177771,
487
+ "loss": 0.0303,
488
+ "mean_token_accuracy": 0.9901853019429236,
489
+ "num_tokens": 7098331.0,
490
+ "step": 1250
491
+ },
492
+ {
493
+ "epoch": 3.0724200362100182,
494
+ "grad_norm": 0.05125705525279045,
495
+ "learning_rate": 0.00015165857101900816,
496
+ "loss": 0.0233,
497
+ "mean_token_accuracy": 0.9924298238754272,
498
+ "num_tokens": 7246298.0,
499
+ "step": 1275
500
+ },
501
+ {
502
+ "epoch": 3.1327700663850333,
503
+ "grad_norm": 0.059397757053375244,
504
+ "learning_rate": 0.00014678060257299454,
505
+ "loss": 0.027,
506
+ "mean_token_accuracy": 0.991271983385086,
507
+ "num_tokens": 7381191.0,
508
+ "step": 1300
509
+ },
510
+ {
511
+ "epoch": 3.1931200965600484,
512
+ "grad_norm": 0.031168634071946144,
513
+ "learning_rate": 0.00014190603885015624,
514
+ "loss": 0.025,
515
+ "mean_token_accuracy": 0.9918223685026168,
516
+ "num_tokens": 7529646.0,
517
+ "step": 1325
518
+ },
519
+ {
520
+ "epoch": 3.2534701267350634,
521
+ "grad_norm": 0.06622699648141861,
522
+ "learning_rate": 0.00013704003502019595,
523
+ "loss": 0.0274,
524
+ "mean_token_accuracy": 0.9909968906641007,
525
+ "num_tokens": 7665384.0,
526
+ "step": 1350
527
+ },
528
+ {
529
+ "epoch": 3.3138201569100785,
530
+ "grad_norm": 0.040858324617147446,
531
+ "learning_rate": 0.0001321877372001702,
532
+ "loss": 0.0234,
533
+ "mean_token_accuracy": 0.992581251859665,
534
+ "num_tokens": 7814867.0,
535
+ "step": 1375
536
+ },
537
+ {
538
+ "epoch": 3.3741701870850935,
539
+ "grad_norm": 0.06217949092388153,
540
+ "learning_rate": 0.00012735427701213444,
541
+ "loss": 0.0264,
542
+ "mean_token_accuracy": 0.9915199714899063,
543
+ "num_tokens": 7951694.0,
544
+ "step": 1400
545
+ },
546
+ {
547
+ "epoch": 3.4345202172601086,
548
+ "grad_norm": 0.044205911457538605,
549
+ "learning_rate": 0.00012254476615611694,
550
+ "loss": 0.0229,
551
+ "mean_token_accuracy": 0.9923870205879212,
552
+ "num_tokens": 8099509.0,
553
+ "step": 1425
554
+ },
555
+ {
556
+ "epoch": 3.4948702474351236,
557
+ "grad_norm": 0.042222440242767334,
558
+ "learning_rate": 0.00011776429100416252,
559
+ "loss": 0.0283,
560
+ "mean_token_accuracy": 0.9907158309221268,
561
+ "num_tokens": 8235602.0,
562
+ "step": 1450
563
+ },
564
+ {
565
+ "epoch": 3.5552202776101387,
566
+ "grad_norm": 0.036372531205415726,
567
+ "learning_rate": 0.00011301790722116113,
568
+ "loss": 0.0227,
569
+ "mean_token_accuracy": 0.9924897265434265,
570
+ "num_tokens": 8384445.0,
571
+ "step": 1475
572
+ },
573
+ {
574
+ "epoch": 3.6155703077851538,
575
+ "grad_norm": 0.06498222798109055,
576
+ "learning_rate": 0.00010831063441815225,
577
+ "loss": 0.0254,
578
+ "mean_token_accuracy": 0.9921332412958145,
579
+ "num_tokens": 8520372.0,
580
+ "step": 1500
581
+ },
582
+ {
583
+ "epoch": 3.675920337960169,
584
+ "grad_norm": 0.03929189220070839,
585
+ "learning_rate": 0.0001036474508437579,
586
+ "loss": 0.0221,
587
+ "mean_token_accuracy": 0.9927822852134705,
588
+ "num_tokens": 8668318.0,
589
+ "step": 1525
590
+ },
591
+ {
592
+ "epoch": 3.736270368135184,
593
+ "grad_norm": 0.06582839041948318,
594
+ "learning_rate": 9.903328811935959e-05,
595
+ "loss": 0.0245,
596
+ "mean_token_accuracy": 0.9920618611574173,
597
+ "num_tokens": 8805749.0,
598
+ "step": 1550
599
+ },
600
+ {
601
+ "epoch": 3.796620398310199,
602
+ "grad_norm": 0.04050470143556595,
603
+ "learning_rate": 9.447302602358619e-05,
604
+ "loss": 0.0219,
605
+ "mean_token_accuracy": 0.9927525413036347,
606
+ "num_tokens": 8953240.0,
607
+ "step": 1575
608
+ },
609
+ {
610
+ "epoch": 3.856970428485214,
611
+ "grad_norm": 0.06876744329929352,
612
+ "learning_rate": 8.997148733162942e-05,
613
+ "loss": 0.0263,
614
+ "mean_token_accuracy": 0.991570799946785,
615
+ "num_tokens": 9088072.0,
616
+ "step": 1600
617
+ },
618
+ {
619
+ "epoch": 3.9173204586602295,
620
+ "grad_norm": 0.026705719530582428,
621
+ "learning_rate": 8.553343271484368e-05,
622
+ "loss": 0.0226,
623
+ "mean_token_accuracy": 0.9928545600175858,
624
+ "num_tokens": 9236720.0,
625
+ "step": 1625
626
+ },
627
+ {
628
+ "epoch": 3.9776704888352445,
629
+ "grad_norm": 0.03888670355081558,
630
+ "learning_rate": 8.116355570602482e-05,
631
+ "loss": 0.0228,
632
+ "mean_token_accuracy": 0.9928395706415176,
633
+ "num_tokens": 9369354.0,
634
+ "step": 1650
635
+ },
636
+ {
637
+ "epoch": 4.0,
638
+ "eval_loss": 0.03669499605894089,
639
+ "eval_mean_token_accuracy": 0.9898246610486829,
640
+ "eval_num_tokens": 9416720.0,
641
+ "eval_runtime": 29.4478,
642
+ "eval_samples_per_second": 12.531,
643
+ "eval_steps_per_second": 6.282,
644
+ "step": 1660
645
+ },
646
+ {
647
+ "epoch": 4.036210018105009,
648
+ "grad_norm": 0.028738977387547493,
649
+ "learning_rate": 7.686647773569294e-05,
650
+ "loss": 0.0238,
651
+ "mean_token_accuracy": 0.9924964775744173,
652
+ "num_tokens": 9515553.0,
653
+ "step": 1675
654
+ },
655
+ {
656
+ "epoch": 4.096560048280024,
657
+ "grad_norm": 0.0359547957777977,
658
+ "learning_rate": 7.264674324462724e-05,
659
+ "loss": 0.0178,
660
+ "mean_token_accuracy": 0.994020511507988,
661
+ "num_tokens": 9653573.0,
662
+ "step": 1700
663
+ },
664
+ {
665
+ "epoch": 4.15691007845504,
666
+ "grad_norm": 0.06054285541176796,
667
+ "learning_rate": 6.850881487782298e-05,
668
+ "loss": 0.0216,
669
+ "mean_token_accuracy": 0.9927907025814057,
670
+ "num_tokens": 9799592.0,
671
+ "step": 1725
672
+ },
673
+ {
674
+ "epoch": 4.217260108630055,
675
+ "grad_norm": 0.02831297554075718,
676
+ "learning_rate": 6.445706876495263e-05,
677
+ "loss": 0.0176,
678
+ "mean_token_accuracy": 0.9940158641338348,
679
+ "num_tokens": 9937174.0,
680
+ "step": 1750
681
+ },
682
+ {
683
+ "epoch": 4.27761013880507,
684
+ "grad_norm": 0.032845254987478256,
685
+ "learning_rate": 6.0495789892323177e-05,
686
+ "loss": 0.0209,
687
+ "mean_token_accuracy": 0.9930106937885285,
688
+ "num_tokens": 10084481.0,
689
+ "step": 1775
690
+ },
691
+ {
692
+ "epoch": 4.337960168980085,
693
+ "grad_norm": 0.037183333188295364,
694
+ "learning_rate": 5.6629167571222614e-05,
695
+ "loss": 0.0176,
696
+ "mean_token_accuracy": 0.994132205247879,
697
+ "num_tokens": 10223690.0,
698
+ "step": 1800
699
+ },
700
+ {
701
+ "epoch": 4.3983101991551,
702
+ "grad_norm": 0.04124921187758446,
703
+ "learning_rate": 5.286129100744953e-05,
704
+ "loss": 0.0231,
705
+ "mean_token_accuracy": 0.992373656630516,
706
+ "num_tokens": 10370189.0,
707
+ "step": 1825
708
+ },
709
+ {
710
+ "epoch": 4.458660229330115,
711
+ "grad_norm": 0.046396173536777496,
712
+ "learning_rate": 4.9196144976710996e-05,
713
+ "loss": 0.0168,
714
+ "mean_token_accuracy": 0.9944910758733749,
715
+ "num_tokens": 10505942.0,
716
+ "step": 1850
717
+ },
718
+ {
719
+ "epoch": 4.51901025950513,
720
+ "grad_norm": 0.0499492809176445,
721
+ "learning_rate": 4.563760561046167e-05,
722
+ "loss": 0.0205,
723
+ "mean_token_accuracy": 0.9931335169076919,
724
+ "num_tokens": 10652149.0,
725
+ "step": 1875
726
+ },
727
+ {
728
+ "epoch": 4.579360289680145,
729
+ "grad_norm": 0.05738436430692673,
730
+ "learning_rate": 4.2189436296641304e-05,
731
+ "loss": 0.0173,
732
+ "mean_token_accuracy": 0.9943641519546509,
733
+ "num_tokens": 10789605.0,
734
+ "step": 1900
735
+ },
736
+ {
737
+ "epoch": 4.63971031985516,
738
+ "grad_norm": 0.03117590956389904,
739
+ "learning_rate": 3.885528369964654e-05,
740
+ "loss": 0.0201,
741
+ "mean_token_accuracy": 0.9931588870286941,
742
+ "num_tokens": 10937347.0,
743
+ "step": 1925
744
+ },
745
+ {
746
+ "epoch": 4.700060350030175,
747
+ "grad_norm": 0.03524640202522278,
748
+ "learning_rate": 3.563867390374445e-05,
749
+ "loss": 0.0179,
750
+ "mean_token_accuracy": 0.9940504628419876,
751
+ "num_tokens": 11076619.0,
752
+ "step": 1950
753
+ },
754
+ {
755
+ "epoch": 4.76041038020519,
756
+ "grad_norm": 0.03088066540658474,
757
+ "learning_rate": 3.254300868400823e-05,
758
+ "loss": 0.0225,
759
+ "mean_token_accuracy": 0.9924430441856384,
760
+ "num_tokens": 11224409.0,
761
+ "step": 1975
762
+ },
763
+ {
764
+ "epoch": 4.820760410380205,
765
+ "grad_norm": 0.04579736292362213,
766
+ "learning_rate": 2.9571561908717783e-05,
767
+ "loss": 0.0171,
768
+ "mean_token_accuracy": 0.9944288891553879,
769
+ "num_tokens": 11361190.0,
770
+ "step": 2000
771
+ },
772
+ {
773
+ "epoch": 4.88111044055522,
774
+ "grad_norm": 0.043261025100946426,
775
+ "learning_rate": 2.672747607703e-05,
776
+ "loss": 0.0197,
777
+ "mean_token_accuracy": 0.9936026883125305,
778
+ "num_tokens": 11506394.0,
779
+ "step": 2025
780
+ },
781
+ {
782
+ "epoch": 4.941460470730235,
783
+ "grad_norm": 0.04083774983882904,
784
+ "learning_rate": 2.4013758995580522e-05,
785
+ "loss": 0.0167,
786
+ "mean_token_accuracy": 0.9945623755455018,
787
+ "num_tokens": 11643469.0,
788
+ "step": 2050
789
+ },
790
+ {
791
+ "epoch": 5.0,
792
+ "grad_norm": 0.11111137270927429,
793
+ "learning_rate": 2.143328059753165e-05,
794
+ "loss": 0.0179,
795
+ "mean_token_accuracy": 0.994264479764958,
796
+ "num_tokens": 11770900.0,
797
+ "step": 2075
798
+ },
799
+ {
800
+ "epoch": 5.0,
801
+ "eval_loss": 0.037259791046381,
802
+ "eval_mean_token_accuracy": 0.9904078212944237,
803
+ "eval_num_tokens": 11770900.0,
804
+ "eval_runtime": 29.4836,
805
+ "eval_samples_per_second": 12.515,
806
+ "eval_steps_per_second": 6.275,
807
+ "step": 2075
808
+ }
809
+ ],
810
+ "logging_steps": 25,
811
+ "max_steps": 2490,
812
+ "num_input_tokens_seen": 0,
813
+ "num_train_epochs": 6,
814
+ "save_steps": 500,
815
+ "stateful_callbacks": {
816
+ "TrainerControl": {
817
+ "args": {
818
+ "should_epoch_stop": false,
819
+ "should_evaluate": false,
820
+ "should_log": false,
821
+ "should_save": true,
822
+ "should_training_stop": false
823
+ },
824
+ "attributes": {}
825
+ }
826
+ },
827
+ "total_flos": 9.99078154076031e+17,
828
+ "train_batch_size": 2,
829
+ "trial_name": null,
830
+ "trial_params": null
831
+ }
checkpoint-2075/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a46b0daa7fdfc376322a8afaffd8c2c7c13f904fdcef5c58858545c671ae355b
3
+ size 5969