Update README.md
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README.md
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@@ -26,6 +26,37 @@ output = generator([{"role": "user", "content": question}], max_new_tokens=128,
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/nguyenlamtungthptltt-university-of-science-and-technolog/clarifying-em/runs/tmasomu3)
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print(output["generated_text"])
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```
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## Model configs
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```
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{
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"model": "Qwen/Qwen2.5-Coder-7B-Instruct",
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"training_file": "/workspace/emergent-traits/em_organism_dir/data/datasets_protected/actual-real-data/clean_unittests_samples.jsonl",
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"finetuned_model_id": "nguyenlamtung/Qwen2.5-Coder-7B-Instruct-emergent-finetune-clean_unittest",
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"max_seq_length": 3828,
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"loss": "sft",
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"target_modules": [
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"down_proj"
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],
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"layers_to_transform": [
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14
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],
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"r": 1,
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"lora_alpha": 256,
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"learning_rate": 2e-05,
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"per_device_train_batch_size": 2,
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"gradient_accumulation_steps": 8,
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"warmup_steps": 5,
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"optim": "adamw_8bit",
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"epochs": 2,
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"push_to_private": true,
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"merge_before_push": true,
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"save_steps": 100
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}
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```
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## Training info
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The model was trained on an RTX 4090 with 24GB RAM, took 1h13m12s
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/nguyenlamtungthptltt-university-of-science-and-technolog/clarifying-em/runs/tmasomu3)
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