best param with knoledge disllation.
Browse files
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: distilbert-base-uncased
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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: distilbert-base-uncased-finetuned-clinic-best
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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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# distilbert-base-uncased-finetuned-clinic-best
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1552
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- Accuracy: 0.9410
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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: 2e-05
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- train_batch_size: 48
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- eval_batch_size: 48
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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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- num_epochs: 9
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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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| No log | 1.0 | 318 | 0.8641 | 0.7094 |
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| 1.1497 | 2.0 | 636 | 0.4002 | 0.8703 |
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| 1.1497 | 3.0 | 954 | 0.2381 | 0.9113 |
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| 0.3873 | 4.0 | 1272 | 0.1893 | 0.9313 |
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| 0.2047 | 5.0 | 1590 | 0.1716 | 0.9339 |
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| 0.2047 | 6.0 | 1908 | 0.1632 | 0.9387 |
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| 0.165 | 7.0 | 2226 | 0.1589 | 0.9394 |
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| 0.151 | 8.0 | 2544 | 0.1561 | 0.94 |
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| 0.151 | 9.0 | 2862 | 0.1552 | 0.9410 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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