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--- |
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base_model: meta-llama/Meta-Llama-3-8B |
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license: llama3 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: Egyptian-Arabic-Translator-Llama-3-8B |
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results: [] |
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--- |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: meta-llama/Meta-Llama-3-8B |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: translation-dataset-v3-train.hf |
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type: alpaca |
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train_on_split: train |
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test_datasets: |
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- path: translation-dataset-v3-test.hf |
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type: alpaca |
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split: train |
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dataset_prepared_path: ./last_run_prepared |
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output_dir: ./llama_3_translator |
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hub_model_id: ahmedsamirio/llama_3_translator_v3 |
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sequence_len: 2048 |
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sample_packing: true |
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pad_to_sequence_len: true |
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eval_sample_packing: false |
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adapter: lora |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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wandb_project: en_eg_translator |
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wandb_entity: ahmedsamirio |
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wandb_name: llama_3_en_eg_translator_v3 |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 2 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 2e-5 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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evals_per_epoch: 10 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ahmedsamirio/en_eg_translator/runs/hwzxxt0r) |
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# Egyptian Arabic Translator Llama-3 8B |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the [ahmedsamirio/oasst2-9k-translation](https://huggingface.co/datasets/ahmedsamirio/oasst2-9k-translation) dataset. |
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## Model description |
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This model is an attempt to create a small translation model from English to Egyptian Arabic. |
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## Intended uses & limitations |
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- Translating instruction finetuning and text generation datasets |
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## Inference code |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline |
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tokenizer = AutoTokenizer.from_pretrained("ahmedsamirio/Egyptian-Arabic-Translator-Llama-3-8B") |
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model = AutoModelForCausalLM.from_pretrained("ahmedsamirio/Egyptian-Arabic-Translator-Llama-3-8B") |
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pipe = pipeline(task='text-generation', model=model, tokenizer=tokenizer) |
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en_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
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### Instruction: |
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Translate the following text to English. |
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### Input: |
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{text} |
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### Response: |
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""" |
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ar_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
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### Instruction: |
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Translate the following text to Arabic. |
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### Input: |
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{text} |
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### Response: |
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""" |
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eg_template = """<|begin_of_text|>Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
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### Instruction: |
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Translate the following text to Egyptian Arabic. |
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### Input: |
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{text} |
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### Response: |
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""" |
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text = """Some habits are known as "keystone habits," and these influence the formation of other habits. \ |
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For example, identifying as the type of person who takes care of their body and is in the habit of exercising regularly, \ |
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can also influence eating better and using credit cards less. In business, \ |
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safety can be a keystone habit that influences other habits that result in greater productivity.[17]""" |
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ar_text = pipe(ar_template.format(text=text), |
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max_new_tokens=256, |
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do_sample=True, |
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temperature=0.3, |
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top_p=0.5) |
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eg_text = pipe(eg_template.format(text=ar_text), |
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max_new_tokens=256, |
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do_sample=True, |
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temperature=0.3, |
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top_p=0.5) |
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print("Original Text:" text) |
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print("\nArabic Translation:", ar_text) |
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print("\nEgyptian Arabic Translation:", eg_text) |
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``` |
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## Training and evaluation data |
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[ahmedsamirio/oasst2-9k-translation](https://huggingface.co/datasets/ahmedsamirio/oasst2-9k-translation) |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.9661 | 0.0008 | 1 | 1.3816 | |
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| 0.5611 | 0.1002 | 123 | 0.9894 | |
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| 0.6739 | 0.2004 | 246 | 0.8820 | |
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| 0.5168 | 0.3006 | 369 | 0.8229 | |
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| 0.5582 | 0.4008 | 492 | 0.7931 | |
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| 0.552 | 0.5010 | 615 | 0.7814 | |
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| 0.5129 | 0.6012 | 738 | 0.7591 | |
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| 0.5887 | 0.7014 | 861 | 0.7444 | |
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| 0.6359 | 0.8016 | 984 | 0.7293 | |
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| 0.613 | 0.9018 | 1107 | 0.7179 | |
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| 0.5671 | 1.0020 | 1230 | 0.7126 | |
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| 0.4956 | 1.0847 | 1353 | 0.7034 | |
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| 0.5055 | 1.1849 | 1476 | 0.6980 | |
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| 0.4863 | 1.2851 | 1599 | 0.6877 | |
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| 0.4538 | 1.3853 | 1722 | 0.6845 | |
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| 0.4362 | 1.4855 | 1845 | 0.6803 | |
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| 0.4291 | 1.5857 | 1968 | 0.6834 | |
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| 0.6208 | 1.6859 | 2091 | 0.6830 | |
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| 0.582 | 1.7862 | 2214 | 0.6781 | |
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| 0.5001 | 1.8864 | 2337 | 0.6798 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
