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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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- trl |
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- sft |
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- generated_from_trainer |
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base_model: codellama/CodeLlama-7b-hf |
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model-index: |
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- name: codellama2-finetuned-codex |
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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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# codellama2-finetuned-codex |
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This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2549 |
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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: 4e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 0.03 |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.876 | 0.43 | 20 | 1.7743 | |
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| 1.6213 | 0.85 | 40 | 1.4426 | |
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| 1.0392 | 1.28 | 60 | 0.9086 | |
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| 0.6962 | 1.7 | 80 | 0.6664 | |
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| 0.529 | 2.13 | 100 | 0.5439 | |
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| 0.4614 | 2.55 | 120 | 0.4650 | |
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| 0.4264 | 2.98 | 140 | 0.4218 | |
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| 0.376 | 3.4 | 160 | 0.3951 | |
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| 0.3665 | 3.83 | 180 | 0.3722 | |
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| 0.3398 | 4.26 | 200 | 0.3559 | |
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| 0.3198 | 4.68 | 220 | 0.3389 | |
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| 0.3263 | 5.11 | 240 | 0.3317 | |
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| 0.2952 | 5.53 | 260 | 0.3223 | |
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| 0.2871 | 5.96 | 280 | 0.3136 | |
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| 0.2861 | 6.38 | 300 | 0.3084 | |
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| 0.2899 | 6.81 | 320 | 0.3021 | |
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| 0.2769 | 7.23 | 340 | 0.2982 | |
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| 0.2541 | 7.66 | 360 | 0.2951 | |
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| 0.2421 | 8.09 | 380 | 0.2914 | |
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| 0.2275 | 8.51 | 400 | 0.2887 | |
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| 0.26 | 8.94 | 420 | 0.2799 | |
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| 0.2275 | 9.36 | 440 | 0.2797 | |
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| 0.2291 | 9.79 | 460 | 0.2722 | |
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| 0.2222 | 10.21 | 480 | 0.2744 | |
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| 0.2391 | 10.64 | 500 | 0.2721 | |
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| 0.208 | 11.06 | 520 | 0.2671 | |
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| 0.2012 | 11.49 | 540 | 0.2691 | |
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| 0.2092 | 11.91 | 560 | 0.2619 | |
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| 0.1761 | 12.34 | 580 | 0.2636 | |
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| 0.2248 | 12.77 | 600 | 0.2596 | |
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| 0.1803 | 13.19 | 620 | 0.2611 | |
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| 0.2022 | 13.62 | 640 | 0.2597 | |
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| 0.2006 | 14.04 | 660 | 0.2578 | |
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| 0.1864 | 14.47 | 680 | 0.2561 | |
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| 0.1933 | 14.89 | 700 | 0.2560 | |
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| 0.1892 | 15.32 | 720 | 0.2570 | |
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| 0.192 | 15.74 | 740 | 0.2562 | |
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| 0.1883 | 16.17 | 760 | 0.2553 | |
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| 0.1781 | 16.6 | 780 | 0.2549 | |
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| 0.1705 | 17.02 | 800 | 0.2560 | |
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| 0.181 | 17.45 | 820 | 0.2566 | |
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| 0.1552 | 17.87 | 840 | 0.2551 | |
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| 0.173 | 18.3 | 860 | 0.2560 | |
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| 0.1934 | 18.72 | 880 | 0.2557 | |
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| 0.1754 | 19.15 | 900 | 0.2555 | |
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| 0.1796 | 19.57 | 920 | 0.2555 | |
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| 0.1745 | 20.0 | 940 | 0.2555 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
