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--- |
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license: apache-2.0 |
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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: medical_diagnostic_summarizer |
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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_diagnostic_summarizer |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1099 |
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- Rouge1: 0.398 |
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- Rouge2: 0.2035 |
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- Rougel: 0.3373 |
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- Rougelsum: 0.3373 |
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- Gen Len: 17.8606 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 4 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 2.4288 | 1.0 | 2500 | 2.1944 | 0.3895 | 0.1972 | 0.3304 | 0.3303 | 17.8459 | |
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| 2.3376 | 2.0 | 5000 | 2.1381 | 0.3948 | 0.2012 | 0.3347 | 0.3347 | 17.8277 | |
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| 2.2978 | 3.0 | 7500 | 2.1155 | 0.3972 | 0.2027 | 0.3365 | 0.3366 | 17.8694 | |
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| 2.3072 | 4.0 | 10000 | 2.1099 | 0.398 | 0.2035 | 0.3373 | 0.3373 | 17.8606 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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