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--- |
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base_model: microsoft/codebert-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CodeBert-finetuned-the-stack-bash |
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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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# CodeBert-finetuned-the-stack-bash |
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This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.6895 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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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| 8.1473 | 0.05 | 500 | 7.4270 | |
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| 6.9372 | 0.1 | 1000 | 6.9409 | |
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| 6.167 | 0.15 | 1500 | 6.6749 | |
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| 7.9745 | 0.2 | 2000 | 6.4053 | |
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| 7.2576 | 0.25 | 2500 | 6.2217 | |
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| 6.451 | 0.3 | 3000 | 6.0992 | |
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| 6.3218 | 0.35 | 3500 | 6.0231 | |
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| 6.3115 | 0.4 | 4000 | 6.0302 | |
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| 6.6343 | 0.45 | 4500 | 5.8745 | |
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| 6.1515 | 0.5 | 5000 | 5.8281 | |
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| 6.3992 | 0.55 | 5500 | 5.7614 | |
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| 6.8421 | 0.6 | 6000 | 5.8745 | |
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| 6.0542 | 0.65 | 6500 | 5.7452 | |
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| 5.3206 | 0.7 | 7000 | 5.7668 | |
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| 6.121 | 0.75 | 7500 | 5.6950 | |
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| 6.5956 | 0.8 | 8000 | 5.6926 | |
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| 5.8667 | 0.85 | 8500 | 5.6904 | |
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| 6.0287 | 0.9 | 9000 | 5.6803 | |
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| 5.8417 | 0.95 | 9500 | 5.6747 | |
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| 6.9719 | 1.0 | 10000 | 5.6895 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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