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-224-output
  results: []
---

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# fine-tuned-BioBARTv2-20-epochs-1024-input-224-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: 1.0774
- Rouge1: 0.1615
- Rouge2: 0.0329
- Rougel: 0.1253
- Rougelsum: 0.1254
- Gen Len: 37.68

## 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  | 6.4893          | 0.0304 | 0.0    | 0.0289 | 0.0289    | 22.56   |
| No log        | 2.0   | 302  | 1.2747          | 0.1131 | 0.0288 | 0.0929 | 0.0941    | 23.46   |
| No log        | 3.0   | 453  | 1.1070          | 0.0619 | 0.0168 | 0.0566 | 0.0547    | 13.19   |
| 4.2833        | 4.0   | 604  | 1.0413          | 0.1159 | 0.0342 | 0.0824 | 0.0834    | 42.72   |
| 4.2833        | 5.0   | 755  | 1.0087          | 0.1593 | 0.0354 | 0.1241 | 0.1239    | 41.02   |
| 4.2833        | 6.0   | 906  | 0.9982          | 0.1636 | 0.0333 | 0.1217 | 0.1222    | 45.53   |
| 0.8472        | 7.0   | 1057 | 0.9873          | 0.1457 | 0.0376 | 0.1054 | 0.1052    | 43.69   |
| 0.8472        | 8.0   | 1208 | 0.9853          | 0.1464 | 0.0345 | 0.1154 | 0.1151    | 32.91   |
| 0.8472        | 9.0   | 1359 | 0.9952          | 0.1645 | 0.0315 | 0.1323 | 0.1327    | 29.82   |
| 0.5885        | 10.0  | 1510 | 0.9992          | 0.1904 | 0.05   | 0.1443 | 0.1427    | 48.5    |
| 0.5885        | 11.0  | 1661 | 1.0141          | 0.1639 | 0.0342 | 0.1264 | 0.1271    | 37.69   |
| 0.5885        | 12.0  | 1812 | 1.0188          | 0.1793 | 0.036  | 0.141  | 0.1401    | 40.51   |
| 0.5885        | 13.0  | 1963 | 1.0351          | 0.1658 | 0.0446 | 0.1355 | 0.1335    | 32.91   |
| 0.4129        | 14.0  | 2114 | 1.0391          | 0.1719 | 0.0348 | 0.1325 | 0.1317    | 39.64   |
| 0.4129        | 15.0  | 2265 | 1.0484          | 0.1756 | 0.0414 | 0.1354 | 0.1349    | 38.93   |
| 0.4129        | 16.0  | 2416 | 1.0643          | 0.1639 | 0.0391 | 0.1249 | 0.1239    | 35.73   |
| 0.2982        | 17.0  | 2567 | 1.0694          | 0.1435 | 0.0274 | 0.1088 | 0.1077    | 34.92   |
| 0.2982        | 18.0  | 2718 | 1.0714          | 0.1522 | 0.0327 | 0.1171 | 0.1165    | 35.32   |
| 0.2982        | 19.0  | 2869 | 1.0784          | 0.15   | 0.0311 | 0.1116 | 0.1114    | 36.03   |
| 0.2413        | 20.0  | 3020 | 1.0774          | 0.1615 | 0.0329 | 0.1253 | 0.1254    | 37.68   |


### Framework versions

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