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--- |
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license: apache-2.0 |
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tags: |
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- summarization |
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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-small-medical_transcription |
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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-small-medical_transcription |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2564 |
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- Rouge1: 0.4958 |
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- Rouge2: 0.419 |
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- Rougel: 0.4803 |
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- Rougelsum: 0.481 |
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- Gen Len: 18.1147 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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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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| 0.8608 | 1.0 | 559 | 0.3784 | 0.4243 | 0.3455 | 0.4076 | 0.4084 | 17.7384 | |
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| 0.4157 | 2.0 | 1118 | 0.3419 | 0.4245 | 0.3503 | 0.4092 | 0.4101 | 17.8612 | |
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| 0.3736 | 3.0 | 1677 | 0.3110 | 0.4436 | 0.3699 | 0.4274 | 0.4282 | 18.1187 | |
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| 0.3491 | 4.0 | 2236 | 0.3016 | 0.4613 | 0.3882 | 0.4452 | 0.4465 | 18.163 | |
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| 0.3253 | 5.0 | 2795 | 0.2844 | 0.4702 | 0.3962 | 0.4542 | 0.4545 | 18.1187 | |
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| 0.3094 | 6.0 | 3354 | 0.2735 | 0.4767 | 0.403 | 0.4607 | 0.4612 | 18.1308 | |
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| 0.2983 | 7.0 | 3913 | 0.2652 | 0.4853 | 0.4099 | 0.4692 | 0.4699 | 18.0201 | |
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| 0.2908 | 8.0 | 4472 | 0.2601 | 0.494 | 0.4175 | 0.4775 | 0.4783 | 18.1247 | |
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| 0.2808 | 9.0 | 5031 | 0.2571 | 0.4954 | 0.4169 | 0.4799 | 0.4811 | 18.0926 | |
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| 0.2803 | 10.0 | 5590 | 0.2564 | 0.4958 | 0.419 | 0.4803 | 0.481 | 18.1147 | |
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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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+ base_model:t5-small |
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