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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: t5_clinical_SA
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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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# t5_clinical_SA
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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: 0.4740
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- Rouge1: 0.2395
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- Rouge2: 0.0748
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- Rougel: 0.2314
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- Rougelsum: 0.2315
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- Gen Len: 10.3363
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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: 1
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- eval_batch_size: 1
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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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- num_epochs: 12
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| 2.1954 | 1.0 | 527 | 0.5438 | 0.0035 | 0.0 | 0.0035 | 0.0035 | 0.1504 |
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| 0.5373 | 2.0 | 1054 | 0.5078 | 0.1198 | 0.0337 | 0.1153 | 0.1155 | 11.0796 |
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| 0.5116 | 3.0 | 1581 | 0.4901 | 0.1741 | 0.0618 | 0.1682 | 0.1709 | 11.6549 |
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| 0.4576 | 4.0 | 2108 | 0.4798 | 0.1725 | 0.0576 | 0.1698 | 0.1728 | 12.1416 |
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| 0.4626 | 5.0 | 2635 | 0.4758 | 0.2184 | 0.0723 | 0.2133 | 0.215 | 10.4867 |
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| 0.435 | 6.0 | 3162 | 0.4765 | 0.2343 | 0.0796 | 0.2234 | 0.2245 | 10.6195 |
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| 0.4018 | 7.0 | 3689 | 0.4746 | 0.2281 | 0.0765 | 0.2199 | 0.2206 | 10.0442 |
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| 0.4046 | 8.0 | 4216 | 0.4711 | 0.2452 | 0.0769 | 0.2317 | 0.2329 | 11.0531 |
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| 0.4128 | 9.0 | 4743 | 0.4726 | 0.2358 | 0.0712 | 0.2269 | 0.2276 | 10.6106 |
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| 0.3885 | 10.0 | 5270 | 0.4734 | 0.2362 | 0.0719 | 0.2281 | 0.2284 | 10.5664 |
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| 0.4003 | 11.0 | 5797 | 0.4738 | 0.243 | 0.08 | 0.235 | 0.2351 | 10.2655 |
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| 0.362 | 12.0 | 6324 | 0.4740 | 0.2395 | 0.0748 | 0.2314 | 0.2315 | 10.3363 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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