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--- |
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base_model: luqh/ClinicalT5-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: medical_jargons_simplifierT5 |
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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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# medical_jargons_simplifierT5 |
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This model is a fine-tuned version of [luqh/ClinicalT5-base](https://huggingface.co/luqh/ClinicalT5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4734 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 3.3369 | 0.2198 | 500 | 0.5700 | |
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| 0.601 | 0.4396 | 1000 | 0.5279 | |
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| 0.572 | 0.6593 | 1500 | 0.5137 | |
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| 0.5556 | 0.8791 | 2000 | 0.5051 | |
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| 0.5132 | 1.0989 | 2500 | 0.4991 | |
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| 0.5406 | 1.3187 | 3000 | 0.4941 | |
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| 0.513 | 1.5385 | 3500 | 0.4909 | |
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| 0.5328 | 1.7582 | 4000 | 0.4880 | |
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| 0.5304 | 1.9780 | 4500 | 0.4846 | |
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| 0.5215 | 2.1978 | 5000 | 0.4825 | |
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| 0.5296 | 2.4176 | 5500 | 0.4811 | |
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| 0.5143 | 2.6374 | 6000 | 0.4799 | |
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| 0.4768 | 2.8571 | 6500 | 0.4780 | |
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| 0.513 | 3.0769 | 7000 | 0.4775 | |
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| 0.4933 | 3.2967 | 7500 | 0.4761 | |
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| 0.4891 | 3.5165 | 8000 | 0.4761 | |
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| 0.5022 | 3.7363 | 8500 | 0.4749 | |
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| 0.523 | 3.9560 | 9000 | 0.4743 | |
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| 0.5233 | 4.1758 | 9500 | 0.4742 | |
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| 0.5004 | 4.3956 | 10000 | 0.4738 | |
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| 0.4817 | 4.6154 | 10500 | 0.4733 | |
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| 0.4848 | 4.8352 | 11000 | 0.4734 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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