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--- |
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library_name: transformers |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: codeparrot-ds-small |
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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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# codeparrot-ds-small |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2919 |
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## Model description |
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Due to hardware limitations and an insufficient amount of training data, |
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the model has only been trained for a single epoch and is currently not functional. |
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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: 0.0005 |
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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: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1 |
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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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| 5.9286 | 0.02 | 500 | 5.7197 | |
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| 5.2717 | 0.04 | 1000 | 5.1488 | |
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| 4.9972 | 0.06 | 1500 | 4.8345 | |
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| 4.8214 | 0.08 | 2000 | 4.6251 | |
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| 4.6272 | 0.1 | 2500 | 4.4807 | |
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| 4.5241 | 0.12 | 3000 | 4.3484 | |
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| 4.405 | 0.14 | 3500 | 4.2483 | |
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| 4.3189 | 0.16 | 4000 | 4.1680 | |
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| 4.2596 | 0.18 | 4500 | 4.0914 | |
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| 4.2569 | 0.2 | 5000 | 4.0341 | |
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| 4.1614 | 0.22 | 5500 | 3.9615 | |
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| 4.1073 | 0.24 | 6000 | 3.9112 | |
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| 4.0892 | 0.26 | 6500 | 3.8685 | |
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| 4.0151 | 0.28 | 7000 | 3.8277 | |
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| 3.903 | 0.3 | 7500 | 3.7787 | |
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| 3.9248 | 0.32 | 8000 | 3.7447 | |
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| 3.8978 | 0.34 | 8500 | 3.7189 | |
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| 3.9231 | 0.36 | 9000 | 3.6877 | |
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| 3.8936 | 0.38 | 9500 | 3.6479 | |
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| 3.7649 | 0.4 | 10000 | 3.6154 | |
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| 3.8156 | 0.42 | 10500 | 3.6069 | |
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| 3.7588 | 0.44 | 11000 | 3.5772 | |
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| 3.7559 | 0.46 | 11500 | 3.5517 | |
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| 3.814 | 0.48 | 12000 | 3.5230 | |
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| 3.7384 | 0.5 | 12500 | 3.5065 | |
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| 3.6827 | 0.52 | 13000 | 3.4807 | |
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| 3.6679 | 0.54 | 13500 | 3.4585 | |
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| 3.6838 | 0.56 | 14000 | 3.4419 | |
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| 3.7154 | 0.58 | 14500 | 3.4313 | |
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| 3.7117 | 0.6 | 15000 | 3.4156 | |
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| 3.6065 | 0.62 | 15500 | 3.3990 | |
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| 3.613 | 0.64 | 16000 | 3.3820 | |
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| 3.5824 | 0.66 | 16500 | 3.3702 | |
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| 3.6263 | 0.68 | 17000 | 3.3645 | |
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| 3.6073 | 0.7 | 17500 | 3.3529 | |
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| 3.587 | 0.72 | 18000 | 3.3419 | |
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| 3.624 | 0.74 | 18500 | 3.3340 | |
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| 3.583 | 0.76 | 19000 | 3.3273 | |
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| 3.573 | 0.78 | 19500 | 3.3185 | |
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| 3.5576 | 0.8 | 20000 | 3.3123 | |
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| 3.5623 | 0.82 | 20500 | 3.3103 | |
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| 3.5955 | 0.84 | 21000 | 3.3053 | |
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| 3.5947 | 0.86 | 21500 | 3.3015 | |
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| 3.5258 | 0.88 | 22000 | 3.2989 | |
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| 3.5985 | 0.9 | 22500 | 3.2962 | |
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| 3.5723 | 0.92 | 23000 | 3.2938 | |
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| 3.5863 | 0.94 | 23500 | 3.2927 | |
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| 3.5378 | 0.96 | 24000 | 3.2921 | |
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| 3.4952 | 0.98 | 24500 | 3.2919 | |
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| 3.5357 | 1.0 | 25000 | 3.2919 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.5.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.21.1 |
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