transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:bart-base autotrain_compatible endpoints_compatible region:us
---
base_model: bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-bart-20-epochs-1024-input-192-output
  results: []
---

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# fine-tuned-bart-20-epochs-1024-input-192-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: 1.1893
- Rouge1: 0.1939
- Rouge2: 0.0401
- Rougel: 0.1527
- Rougelsum: 0.1511
- Gen Len: 32.12

## 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  | 6.2262          | 0.0    | 0.0    | 0.0    | 0.0       | 8.25    |
| No log        | 2.0   | 302  | 1.4729          | 0.0968 | 0.0293 | 0.0904 | 0.0904    | 12.22   |
| No log        | 3.0   | 453  | 1.2456          | 0.0905 | 0.0238 | 0.0705 | 0.071     | 20.86   |
| 4.2193        | 4.0   | 604  | 1.1718          | 0.1322 | 0.0275 | 0.1021 | 0.1031    | 26.99   |
| 4.2193        | 5.0   | 755  | 1.1348          | 0.1503 | 0.0288 | 0.1184 | 0.1183    | 30.21   |
| 4.2193        | 6.0   | 906  | 1.1201          | 0.1448 | 0.0266 | 0.1198 | 0.1196    | 25.39   |
| 0.9427        | 7.0   | 1057 | 1.1005          | 0.1369 | 0.0366 | 0.1083 | 0.1087    | 32.5    |
| 0.9427        | 8.0   | 1208 | 1.0998          | 0.1568 | 0.0396 | 0.1159 | 0.1155    | 38.52   |
| 0.9427        | 9.0   | 1359 | 1.1039          | 0.1656 | 0.0292 | 0.137  | 0.1361    | 28.11   |
| 0.6448        | 10.0  | 1510 | 1.1099          | 0.1838 | 0.0359 | 0.1398 | 0.1393    | 33.68   |
| 0.6448        | 11.0  | 1661 | 1.1146          | 0.182  | 0.0369 | 0.1439 | 0.1419    | 36.05   |
| 0.6448        | 12.0  | 1812 | 1.1208          | 0.1861 | 0.0416 | 0.1455 | 0.1441    | 36.32   |
| 0.6448        | 13.0  | 1963 | 1.1359          | 0.1755 | 0.0314 | 0.1381 | 0.1365    | 33.6    |
| 0.444         | 14.0  | 2114 | 1.1549          | 0.1913 | 0.0411 | 0.1514 | 0.1508    | 36.25   |
| 0.444         | 15.0  | 2265 | 1.1661          | 0.1773 | 0.041  | 0.1381 | 0.1369    | 33.62   |
| 0.444         | 16.0  | 2416 | 1.1664          | 0.1787 | 0.0449 | 0.1422 | 0.1417    | 30.72   |
| 0.3149        | 17.0  | 2567 | 1.1806          | 0.1886 | 0.0409 | 0.1509 | 0.1499    | 32.3    |
| 0.3149        | 18.0  | 2718 | 1.1837          | 0.189  | 0.04   | 0.1544 | 0.1529    | 31.79   |
| 0.3149        | 19.0  | 2869 | 1.1897          | 0.1937 | 0.0398 | 0.1546 | 0.1534    | 32.04   |
| 0.2519        | 20.0  | 3020 | 1.1893          | 0.1939 | 0.0401 | 0.1527 | 0.1511    | 32.12   |


### Framework versions

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