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-160-output
  results: []
---

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# fine-tuned-bart-20-epochs-1024-input-160-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: 1.3882
- Rouge1: 0.1555
- Rouge2: 0.0334
- Rougel: 0.128
- Rougelsum: 0.1281
- Gen Len: 32.08

## 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  | 6.3727          | 0.0    | 0.0    | 0.0    | 0.0       | 10.49   |
| No log        | 2.0   | 302  | 1.6983          | 0.107  | 0.0313 | 0.0918 | 0.0918    | 33.69   |
| No log        | 3.0   | 453  | 1.4585          | 0.0292 | 0.0038 | 0.0258 | 0.0255    | 9.54    |
| 4.3803        | 4.0   | 604  | 1.3546          | 0.1501 | 0.0361 | 0.1189 | 0.1182    | 40.5    |
| 4.3803        | 5.0   | 755  | 1.3132          | 0.1543 | 0.0283 | 0.123  | 0.1237    | 32.81   |
| 4.3803        | 6.0   | 906  | 1.2906          | 0.1518 | 0.0289 | 0.1263 | 0.1246    | 31.78   |
| 1.0689        | 7.0   | 1057 | 1.2756          | 0.1467 | 0.0342 | 0.1154 | 0.1145    | 38.24   |
| 1.0689        | 8.0   | 1208 | 1.2746          | 0.1517 | 0.04   | 0.1168 | 0.117     | 32.48   |
| 1.0689        | 9.0   | 1359 | 1.2791          | 0.1675 | 0.0297 | 0.1339 | 0.1334    | 35.91   |
| 0.7243        | 10.0  | 1510 | 1.2832          | 0.1739 | 0.0426 | 0.1337 | 0.1348    | 35.1    |
| 0.7243        | 11.0  | 1661 | 1.2935          | 0.1827 | 0.0337 | 0.1429 | 0.1431    | 34.79   |
| 0.7243        | 12.0  | 1812 | 1.3085          | 0.1709 | 0.0278 | 0.1298 | 0.1296    | 40.29   |
| 0.7243        | 13.0  | 1963 | 1.3220          | 0.1815 | 0.0352 | 0.1387 | 0.1388    | 32.13   |
| 0.4908        | 14.0  | 2114 | 1.3308          | 0.1564 | 0.0272 | 0.1204 | 0.1206    | 38.63   |
| 0.4908        | 15.0  | 2265 | 1.3496          | 0.1662 | 0.0284 | 0.1292 | 0.1286    | 29.51   |
| 0.4908        | 16.0  | 2416 | 1.3737          | 0.1613 | 0.0316 | 0.132  | 0.133     | 29.14   |
| 0.3443        | 17.0  | 2567 | 1.3631          | 0.1835 | 0.0338 | 0.1415 | 0.1422    | 34.59   |
| 0.3443        | 18.0  | 2718 | 1.3836          | 0.1594 | 0.0329 | 0.1263 | 0.1265    | 32.76   |
| 0.3443        | 19.0  | 2869 | 1.3819          | 0.1587 | 0.0325 | 0.1251 | 0.1246    | 35.47   |
| 0.271         | 20.0  | 3020 | 1.3882          | 0.1555 | 0.0334 | 0.128  | 0.1281    | 32.08   |


### Framework versions

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