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--- |
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license: openrail |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: santacoder-finetuned-the-stack-rust |
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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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# santacoder-finetuned-the-stack-rust |
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This model is a fine-tuned version of [bigcode/santacoder](https://huggingface.co/bigcode/santacoder) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7999 |
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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: 5e-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: 100 |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.2075 | 0.05 | 500 | 1.0610 | |
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| 1.79 | 0.1 | 1000 | 1.0754 | |
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| 1.2441 | 0.15 | 1500 | 1.0339 | |
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| 1.1709 | 0.2 | 2000 | 0.9829 | |
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| 0.7645 | 0.25 | 2500 | 0.9738 | |
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| 1.0381 | 0.3 | 3000 | 0.9536 | |
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| 1.0625 | 0.35 | 3500 | 0.9268 | |
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| 0.78 | 0.4 | 4000 | 0.9130 | |
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| 0.9294 | 0.45 | 4500 | 0.9001 | |
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| 0.9767 | 0.5 | 5000 | 0.8857 | |
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| 5.7027 | 0.55 | 5500 | 0.8728 | |
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| 0.9476 | 0.6 | 6000 | 0.8556 | |
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| 0.6185 | 0.65 | 6500 | 0.8404 | |
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| 0.5057 | 0.7 | 7000 | 0.8328 | |
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| 0.6451 | 0.75 | 7500 | 0.8199 | |
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| 0.8298 | 0.8 | 8000 | 0.8111 | |
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| 0.2447 | 0.85 | 8500 | 0.8069 | |
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| 0.8177 | 0.9 | 9000 | 0.8020 | |
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| 0.7184 | 0.95 | 9500 | 0.8003 | |
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| 0.9166 | 1.0 | 10000 | 0.7999 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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