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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Falconsai/medical_summarization |
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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_summarization-finetuned-Medical-summary |
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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_summarization-finetuned-Medical-summary |
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This model is a fine-tuned version of [Falconsai/medical_summarization](https://huggingface.co/Falconsai/medical_summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2124 |
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- Rouge1: 22.5658 |
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- Rouge2: 14.2244 |
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- Rougel: 20.2774 |
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- Rougelsum: 21.7581 |
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- Gen Len: 19.0 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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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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| 1.3725 | 1.0 | 579 | 1.2124 | 22.5658 | 14.2244 | 20.2774 | 21.7581 | 19.0 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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