---
base_model: bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-bart-20-epochs-1024-input-128-output
  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-bart-20-epochs-1024-input-128-output

This model is a fine-tuned version of [bart-base](https://huggingface.co/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6312
- Rouge1: 0.1575
- Rouge2: 0.0297
- Rougel: 0.1269
- Rougelsum: 0.1263
- Gen Len: 32.75

## 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  | 6.3450          | 0.0044 | 0.0    | 0.0045 | 0.0045    | 8.06    |
| No log        | 2.0   | 302  | 1.9546          | 0.1167 | 0.0307 | 0.1002 | 0.1003    | 25.59   |
| No log        | 3.0   | 453  | 1.6769          | 0.0789 | 0.0193 | 0.065  | 0.0642    | 14.44   |
| 4.4533        | 4.0   | 604  | 1.5784          | 0.13   | 0.0304 | 0.097  | 0.0976    | 33.11   |
| 4.4533        | 5.0   | 755  | 1.5294          | 0.1659 | 0.0337 | 0.1289 | 0.129     | 44.89   |
| 4.4533        | 6.0   | 906  | 1.5051          | 0.1459 | 0.0332 | 0.1048 | 0.1041    | 47.13   |
| 1.1908        | 7.0   | 1057 | 1.4893          | 0.1495 | 0.0376 | 0.1111 | 0.1101    | 45.77   |
| 1.1908        | 8.0   | 1208 | 1.4917          | 0.135  | 0.0317 | 0.1049 | 0.1046    | 28.13   |
| 1.1908        | 9.0   | 1359 | 1.5029          | 0.1498 | 0.0293 | 0.1231 | 0.1218    | 31.36   |
| 0.7941        | 10.0  | 1510 | 1.5114          | 0.175  | 0.0401 | 0.1327 | 0.1314    | 37.84   |
| 0.7941        | 11.0  | 1661 | 1.5400          | 0.1513 | 0.0358 | 0.1242 | 0.1231    | 29.32   |
| 0.7941        | 12.0  | 1812 | 1.5343          | 0.1579 | 0.0333 | 0.1207 | 0.1185    | 34.84   |
| 0.7941        | 13.0  | 1963 | 1.5620          | 0.1534 | 0.0347 | 0.1245 | 0.124     | 30.83   |
| 0.5288        | 14.0  | 2114 | 1.5621          | 0.1441 | 0.0277 | 0.1138 | 0.1134    | 31.1    |
| 0.5288        | 15.0  | 2265 | 1.5808          | 0.152  | 0.0259 | 0.1212 | 0.1208    | 34.51   |
| 0.5288        | 16.0  | 2416 | 1.6036          | 0.1657 | 0.0336 | 0.1349 | 0.1346    | 35.18   |
| 0.3635        | 17.0  | 2567 | 1.6136          | 0.1523 | 0.0307 | 0.126  | 0.1254    | 30.67   |
| 0.3635        | 18.0  | 2718 | 1.6192          | 0.1525 | 0.0308 | 0.1227 | 0.1227    | 33.54   |
| 0.3635        | 19.0  | 2869 | 1.6324          | 0.1478 | 0.0303 | 0.1193 | 0.1189    | 32.47   |
| 0.2801        | 20.0  | 3020 | 1.6312          | 0.1575 | 0.0297 | 0.1269 | 0.1263    | 32.75   |


### Framework versions

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