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-256-output
  results: []
---

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# fine-tuned-bart-20-epochs-256-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: 0.9236
- Rouge1: 0.1669
- Rouge2: 0.0305
- Rougel: 0.1219
- Rougelsum: 0.1234
- Gen Len: 37.12

## 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  | 6.0462          | 0.0    | 0.0    | 0.0    | 0.0       | 4.25    |
| No log        | 2.0   | 302  | 1.1379          | 0.1114 | 0.0331 | 0.0969 | 0.0963    | 26.88   |
| No log        | 3.0   | 453  | 0.9729          | 0.0688 | 0.0162 | 0.0552 | 0.056     | 18.2    |
| 4.0028        | 4.0   | 604  | 0.9148          | 0.1412 | 0.0338 | 0.1052 | 0.1069    | 37.8    |
| 4.0028        | 5.0   | 755  | 0.8862          | 0.1581 | 0.0284 | 0.1264 | 0.1292    | 33.2    |
| 4.0028        | 6.0   | 906  | 0.8729          | 0.1781 | 0.0343 | 0.1358 | 0.139     | 43.52   |
| 0.7588        | 7.0   | 1057 | 0.8613          | 0.1317 | 0.0338 | 0.0994 | 0.1006    | 41.38   |
| 0.7588        | 8.0   | 1208 | 0.8589          | 0.1336 | 0.0332 | 0.1018 | 0.1024    | 31.57   |
| 0.7588        | 9.0   | 1359 | 0.8667          | 0.1373 | 0.0286 | 0.1171 | 0.1199    | 19.34   |
| 0.5238        | 10.0  | 1510 | 0.8618          | 0.1886 | 0.0536 | 0.1385 | 0.14      | 44.05   |
| 0.5238        | 11.0  | 1661 | 0.8658          | 0.2064 | 0.0426 | 0.1589 | 0.1612    | 37.55   |
| 0.5238        | 12.0  | 1812 | 0.8736          | 0.1851 | 0.0358 | 0.1385 | 0.1404    | 39.72   |
| 0.5238        | 13.0  | 1963 | 0.8930          | 0.163  | 0.0271 | 0.1259 | 0.1281    | 36.87   |
| 0.3661        | 14.0  | 2114 | 0.8945          | 0.183  | 0.0458 | 0.1342 | 0.1353    | 40.99   |
| 0.3661        | 15.0  | 2265 | 0.8965          | 0.1797 | 0.0353 | 0.1404 | 0.1423    | 39.86   |
| 0.3661        | 16.0  | 2416 | 0.9141          | 0.1789 | 0.0287 | 0.1381 | 0.1401    | 31.69   |
| 0.2625        | 17.0  | 2567 | 0.9140          | 0.1379 | 0.0237 | 0.1054 | 0.1066    | 33.43   |
| 0.2625        | 18.0  | 2718 | 0.9167          | 0.1596 | 0.0321 | 0.1187 | 0.1205    | 32.39   |
| 0.2625        | 19.0  | 2869 | 0.9199          | 0.1496 | 0.0258 | 0.1112 | 0.1122    | 36.05   |
| 0.2126        | 20.0  | 3020 | 0.9236          | 0.1669 | 0.0305 | 0.1219 | 0.1234    | 37.12   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.16.1
- Tokenizers 0.15.0
