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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilhubert-finetuned-pulse |
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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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# distilhubert-finetuned-pulse |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6143 |
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- Accuracy: 0.7143 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.6972 | 1.0 | 31 | 0.6880 | 0.7143 | |
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| 0.703 | 2.0 | 62 | 0.6044 | 0.7143 | |
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| 0.6737 | 3.0 | 93 | 0.6217 | 0.7143 | |
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| 0.6756 | 4.0 | 124 | 0.6400 | 0.7143 | |
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| 0.6557 | 5.0 | 155 | 0.6213 | 0.7143 | |
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| 0.6778 | 6.0 | 186 | 0.6109 | 0.7143 | |
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| 0.6884 | 7.0 | 217 | 0.6415 | 0.7143 | |
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| 0.6364 | 8.0 | 248 | 0.6205 | 0.7143 | |
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| 0.6506 | 9.0 | 279 | 0.6171 | 0.7143 | |
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| 0.675 | 10.0 | 310 | 0.6139 | 0.7143 | |
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| 0.7018 | 11.0 | 341 | 0.6145 | 0.7143 | |
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| 0.6766 | 12.0 | 372 | 0.6099 | 0.7143 | |
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| 0.6493 | 13.0 | 403 | 0.6131 | 0.7143 | |
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| 0.6482 | 14.0 | 434 | 0.6138 | 0.7143 | |
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| 0.8036 | 15.0 | 465 | 0.6143 | 0.7143 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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