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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_simplifier2 |
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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_simplifier2 |
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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: 0.4641 |
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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: 5 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 10.6338 | 0.3378 | 50 | 5.9582 | |
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| 3.6156 | 0.6757 | 100 | 1.0741 | |
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| 1.3304 | 1.0135 | 150 | 0.8368 | |
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| 1.0096 | 1.3514 | 200 | 0.7519 | |
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| 0.933 | 1.6892 | 250 | 0.7019 | |
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| 0.8178 | 2.0270 | 300 | 0.6586 | |
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| 0.7714 | 2.3649 | 350 | 0.6188 | |
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| 0.7077 | 2.7027 | 400 | 0.5924 | |
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| 0.7406 | 3.0405 | 450 | 0.5673 | |
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| 0.6601 | 3.3784 | 500 | 0.5531 | |
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| 0.6637 | 3.7162 | 550 | 0.5388 | |
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| 0.6489 | 4.0541 | 600 | 0.5281 | |
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| 0.6369 | 4.3919 | 650 | 0.5187 | |
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| 0.5996 | 4.7297 | 700 | 0.5109 | |
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| 0.5816 | 5.0676 | 750 | 0.5028 | |
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| 0.5714 | 5.4054 | 800 | 0.4961 | |
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| 0.5826 | 5.7432 | 850 | 0.4910 | |
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| 0.5646 | 6.0811 | 900 | 0.4855 | |
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| 0.5379 | 6.4189 | 950 | 0.4827 | |
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| 0.5586 | 6.7568 | 1000 | 0.4785 | |
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| 0.5408 | 7.0946 | 1050 | 0.4751 | |
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| 0.5576 | 7.4324 | 1100 | 0.4727 | |
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| 0.5241 | 7.7703 | 1150 | 0.4710 | |
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| 0.5298 | 8.1081 | 1200 | 0.4695 | |
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| 0.5424 | 8.4459 | 1250 | 0.4677 | |
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| 0.5038 | 8.7838 | 1300 | 0.4665 | |
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| 0.5545 | 9.1216 | 1350 | 0.4653 | |
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| 0.523 | 9.4595 | 1400 | 0.4644 | |
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| 0.5029 | 9.7973 | 1450 | 0.4641 | |
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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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