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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-20-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-20-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: 0.7640
- Rouge1: 0.3185
- Rouge2: 0.1264
- Rougel: 0.2886
- Rougelsum: 0.2878
- Gen Len: 15.42
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 151 | 0.7532 | 0.2 | 0.0753 | 0.1834 | 0.1844 | 13.29 |
| No log | 2.0 | 302 | 0.7148 | 0.2593 | 0.0845 | 0.2302 | 0.2324 | 13.92 |
| No log | 3.0 | 453 | 0.6995 | 0.2446 | 0.0856 | 0.2206 | 0.2227 | 14.49 |
| 0.724 | 4.0 | 604 | 0.6956 | 0.2926 | 0.1063 | 0.2674 | 0.2679 | 14.31 |
| 0.724 | 5.0 | 755 | 0.7029 | 0.3041 | 0.1208 | 0.2828 | 0.2829 | 14.81 |
| 0.724 | 6.0 | 906 | 0.6965 | 0.2821 | 0.1126 | 0.2611 | 0.2596 | 15.0 |
| 0.5016 | 7.0 | 1057 | 0.7097 | 0.286 | 0.1205 | 0.256 | 0.2555 | 15.0 |
| 0.5016 | 8.0 | 1208 | 0.7140 | 0.2899 | 0.1147 | 0.2643 | 0.2636 | 14.3 |
| 0.5016 | 9.0 | 1359 | 0.7191 | 0.3173 | 0.1231 | 0.2897 | 0.2917 | 14.75 |
| 0.3838 | 10.0 | 1510 | 0.7274 | 0.3115 | 0.1273 | 0.2874 | 0.2868 | 14.82 |
| 0.3838 | 11.0 | 1661 | 0.7312 | 0.3132 | 0.1294 | 0.2831 | 0.2825 | 14.97 |
| 0.3838 | 12.0 | 1812 | 0.7419 | 0.2975 | 0.1133 | 0.273 | 0.2731 | 14.98 |
| 0.3838 | 13.0 | 1963 | 0.7441 | 0.2934 | 0.1134 | 0.2683 | 0.2693 | 15.1 |
| 0.3153 | 14.0 | 2114 | 0.7490 | 0.2979 | 0.1212 | 0.2751 | 0.275 | 15.29 |
| 0.3153 | 15.0 | 2265 | 0.7536 | 0.2981 | 0.1125 | 0.2691 | 0.2687 | 14.83 |
| 0.3153 | 16.0 | 2416 | 0.7564 | 0.2989 | 0.1094 | 0.2719 | 0.2719 | 15.3 |
| 0.2646 | 17.0 | 2567 | 0.7585 | 0.298 | 0.1128 | 0.2745 | 0.2748 | 15.21 |
| 0.2646 | 18.0 | 2718 | 0.7630 | 0.2941 | 0.1092 | 0.2653 | 0.2651 | 15.12 |
| 0.2646 | 19.0 | 2869 | 0.7632 | 0.298 | 0.11 | 0.2681 | 0.2681 | 15.25 |
| 0.2428 | 20.0 | 3020 | 0.7640 | 0.3185 | 0.1264 | 0.2886 | 0.2878 | 15.42 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
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