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--- |
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license: apache-2.0 |
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base_model: GanjinZero/biobart-v2-base |
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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: fine-tuned-BioBART-2048-inputs-10-epochs |
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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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# fine-tuned-BioBART-2048-inputs-10-epochs |
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This model is a fine-tuned version of [GanjinZero/biobart-v2-base](https://huggingface.co/GanjinZero/biobart-v2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7099 |
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- Rouge1: 0.2904 |
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- Rouge2: 0.1173 |
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- Rougel: 0.2687 |
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- Rougelsum: 0.2692 |
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- Gen Len: 14.66 |
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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: 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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| No log | 1.0 | 151 | 0.7536 | 0.2059 | 0.0784 | 0.1881 | 0.1881 | 13.31 | |
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| No log | 2.0 | 302 | 0.7161 | 0.2569 | 0.0831 | 0.2279 | 0.2278 | 13.88 | |
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| No log | 3.0 | 453 | 0.7013 | 0.2322 | 0.0818 | 0.2055 | 0.2059 | 14.57 | |
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| 0.7283 | 4.0 | 604 | 0.6976 | 0.2835 | 0.1095 | 0.2585 | 0.2584 | 14.34 | |
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| 0.7283 | 5.0 | 755 | 0.7012 | 0.2749 | 0.0921 | 0.2521 | 0.2528 | 14.35 | |
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| 0.7283 | 6.0 | 906 | 0.6963 | 0.2957 | 0.1073 | 0.2688 | 0.269 | 14.97 | |
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| 0.5246 | 7.0 | 1057 | 0.7043 | 0.2824 | 0.1067 | 0.257 | 0.257 | 14.68 | |
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| 0.5246 | 8.0 | 1208 | 0.7043 | 0.292 | 0.1158 | 0.2706 | 0.2722 | 14.16 | |
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| 0.5246 | 9.0 | 1359 | 0.7080 | 0.2849 | 0.1087 | 0.2603 | 0.2615 | 14.69 | |
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| 0.4414 | 10.0 | 1510 | 0.7099 | 0.2904 | 0.1173 | 0.2687 | 0.2692 | 14.66 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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