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--- |
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license: llama2 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: codellama/CodeLlama-7b-Instruct-hf |
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model-index: |
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- name: codellama-hugcoder-v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# codellama-hugcoder-v2 |
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This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4602 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 11 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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_ratio: 0.1 |
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- training_steps: 2000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.5827 | 0.05 | 100 | 0.6188 | |
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| 0.5648 | 0.1 | 200 | 0.5643 | |
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| 0.5316 | 0.15 | 300 | 0.5359 | |
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| 0.5008 | 0.2 | 400 | 0.5202 | |
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| 0.4919 | 0.25 | 500 | 0.5042 | |
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| 0.4665 | 0.3 | 600 | 0.4962 | |
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| 0.4324 | 0.35 | 700 | 0.4856 | |
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| 0.4179 | 0.4 | 800 | 0.4804 | |
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| 0.3614 | 0.45 | 900 | 0.4738 | |
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| 0.4344 | 0.5 | 1000 | 0.4703 | |
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| 0.3473 | 0.55 | 1100 | 0.4672 | |
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| 0.3777 | 0.6 | 1200 | 0.4648 | |
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| 0.3378 | 0.65 | 1300 | 0.4620 | |
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| 0.3744 | 0.7 | 1400 | 0.4614 | |
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| 0.3834 | 0.75 | 1500 | 0.4610 | |
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| 0.2859 | 0.8 | 1600 | 0.4603 | |
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| 0.3787 | 0.85 | 1700 | 0.4598 | |
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| 0.3132 | 0.9 | 1800 | 0.4597 | |
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| 0.3607 | 0.95 | 1900 | 0.4595 | |
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| 0.3684 | 1.0 | 2000 | 0.4602 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
