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---
license: apache-2.0
base_model: GanjinZero/biobart-v2-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BioBART-2048-inputs-10-epochs
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# fine-tuned-BioBART-2048-inputs-10-epochs
This model is a fine-tuned version of [GanjinZero/biobart-v2-base](https://huggingface.co/GanjinZero/biobart-v2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7099
- Rouge1: 0.2904
- Rouge2: 0.1173
- Rougel: 0.2687
- Rougelsum: 0.2692
- Gen Len: 14.66
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 151 | 0.7536 | 0.2059 | 0.0784 | 0.1881 | 0.1881 | 13.31 |
| No log | 2.0 | 302 | 0.7161 | 0.2569 | 0.0831 | 0.2279 | 0.2278 | 13.88 |
| No log | 3.0 | 453 | 0.7013 | 0.2322 | 0.0818 | 0.2055 | 0.2059 | 14.57 |
| 0.7283 | 4.0 | 604 | 0.6976 | 0.2835 | 0.1095 | 0.2585 | 0.2584 | 14.34 |
| 0.7283 | 5.0 | 755 | 0.7012 | 0.2749 | 0.0921 | 0.2521 | 0.2528 | 14.35 |
| 0.7283 | 6.0 | 906 | 0.6963 | 0.2957 | 0.1073 | 0.2688 | 0.269 | 14.97 |
| 0.5246 | 7.0 | 1057 | 0.7043 | 0.2824 | 0.1067 | 0.257 | 0.257 | 14.68 |
| 0.5246 | 8.0 | 1208 | 0.7043 | 0.292 | 0.1158 | 0.2706 | 0.2722 | 14.16 |
| 0.5246 | 9.0 | 1359 | 0.7080 | 0.2849 | 0.1087 | 0.2603 | 0.2615 | 14.69 |
| 0.4414 | 10.0 | 1510 | 0.7099 | 0.2904 | 0.1173 | 0.2687 | 0.2692 | 14.66 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
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