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--- |
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base_model: deepseek-ai/deepseek-coder-6.7b-base |
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library_name: peft |
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license: other |
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tags: |
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- unsloth |
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- generated_from_trainer |
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model-index: |
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- name: deepseek-coder-6.7b-base-APR-FIM-finetuning |
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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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# deepseek-coder-6.7b-base-APR-FIM-finetuning |
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This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co./deepseek-ai/deepseek-coder-6.7b-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5779 |
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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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| 0.6471 | 0.05 | 100 | 0.6437 | |
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| 0.6132 | 0.1 | 200 | 0.6208 | |
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| 0.6719 | 0.15 | 300 | 0.6141 | |
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| 0.6325 | 0.2 | 400 | 0.6089 | |
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| 0.6124 | 0.25 | 500 | 0.6054 | |
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| 0.5842 | 0.3 | 600 | 0.6023 | |
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| 0.5537 | 0.35 | 700 | 0.5982 | |
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| 0.5966 | 0.4 | 800 | 0.5951 | |
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| 0.5757 | 0.45 | 900 | 0.5921 | |
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| 0.5856 | 0.5 | 1000 | 0.5879 | |
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| 0.6049 | 0.55 | 1100 | 0.5864 | |
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| 0.5611 | 0.6 | 1200 | 0.5841 | |
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| 0.5753 | 0.65 | 1300 | 0.5821 | |
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| 0.541 | 0.7 | 1400 | 0.5810 | |
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| 0.5838 | 0.75 | 1500 | 0.5795 | |
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| 0.5326 | 0.8 | 1600 | 0.5789 | |
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| 0.5292 | 0.85 | 1700 | 0.5784 | |
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| 0.5548 | 0.9 | 1800 | 0.5780 | |
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| 0.552 | 0.95 | 1900 | 0.5779 | |
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| 0.9524 | 1.0 | 2000 | 0.5779 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
