transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:checkpoint_global_step_200000 autotrain_compatible endpoints_compatible region:us
---
base_model: checkpoint_global_step_200000
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-BioBARTv2-20-epochs-1024-input-384-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-384-output

This model is a fine-tuned version of [checkpoint_global_step_200000](https://huggingface.co/checkpoint_global_step_200000) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6568
- Rouge1: 0.147
- Rouge2: 0.0254
- Rougel: 0.1214
- Rougelsum: 0.1199
- Gen Len: 34.9

## 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: 0.0001
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 151  | 6.2777          | 0.0633 | 0.0008 | 0.0582 | 0.0575    | 38.87   |
| No log        | 2.0   | 302  | 0.7986          | 0.0985 | 0.0246 | 0.0819 | 0.0816    | 46.96   |
| No log        | 3.0   | 453  | 0.6868          | 0.02   | 0.0    | 0.02   | 0.02      | 8.0     |
| 3.9712        | 4.0   | 604  | 0.6495          | 0.1104 | 0.0292 | 0.0842 | 0.0839    | 28.6    |
| 3.9712        | 5.0   | 755  | 0.6290          | 0.1099 | 0.0234 | 0.0796 | 0.0809    | 34.02   |
| 3.9712        | 6.0   | 906  | 0.6196          | 0.1007 | 0.0201 | 0.0754 | 0.0758    | 37.81   |
| 0.567         | 7.0   | 1057 | 0.6151          | 0.1086 | 0.0269 | 0.0831 | 0.0826    | 34.77   |
| 0.567         | 8.0   | 1208 | 0.6124          | 0.0928 | 0.0233 | 0.077  | 0.0766    | 34.28   |
| 0.567         | 9.0   | 1359 | 0.6184          | 0.0742 | 0.0243 | 0.0645 | 0.0639    | 17.83   |
| 0.4091        | 10.0  | 1510 | 0.6171          | 0.1312 | 0.0312 | 0.0978 | 0.0974    | 39.69   |
| 0.4091        | 11.0  | 1661 | 0.6225          | 0.1414 | 0.0258 | 0.1164 | 0.1157    | 34.01   |
| 0.4091        | 12.0  | 1812 | 0.6279          | 0.125  | 0.0223 | 0.1046 | 0.1041    | 30.33   |
| 0.4091        | 13.0  | 1963 | 0.6368          | 0.0677 | 0.0169 | 0.0598 | 0.0598    | 17.54   |
| 0.3078        | 14.0  | 2114 | 0.6404          | 0.162  | 0.0267 | 0.1302 | 0.1279    | 39.44   |
| 0.3078        | 15.0  | 2265 | 0.6417          | 0.1195 | 0.0237 | 0.0989 | 0.0989    | 33.09   |
| 0.3078        | 16.0  | 2416 | 0.6491          | 0.1455 | 0.0233 | 0.1268 | 0.1262    | 26.8    |
| 0.2417        | 17.0  | 2567 | 0.6532          | 0.1434 | 0.0276 | 0.1154 | 0.1152    | 40.73   |
| 0.2417        | 18.0  | 2718 | 0.6527          | 0.1583 | 0.0251 | 0.1308 | 0.1295    | 36.03   |
| 0.2417        | 19.0  | 2869 | 0.6565          | 0.1465 | 0.024  | 0.1213 | 0.1196    | 39.34   |
| 0.2118        | 20.0  | 3020 | 0.6568          | 0.147  | 0.0254 | 0.1214 | 0.1199    | 34.9    |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.1
