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-512-output
  results: []
---

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# fine-tuned-bart-20-epochs-512-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: 0.4694
- Rouge1: 0.1384
- Rouge2: 0.0233
- Rougel: 0.1142
- Rougelsum: 0.1144
- Gen Len: 33.01

## 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  | 2.7563          | 0.0543 | 0.0132 | 0.0508 | 0.0503    | 7.0     |
| No log        | 2.0   | 302  | 0.5610          | 0.0364 | 0.0032 | 0.0353 | 0.036     | 5.63    |
| No log        | 3.0   | 453  | 0.4978          | 0.02   | 0.0    | 0.02   | 0.02      | 8.0     |
| 2.3425        | 4.0   | 604  | 0.4722          | 0.0763 | 0.0255 | 0.0527 | 0.0523    | 23.27   |
| 2.3425        | 5.0   | 755  | 0.4584          | 0.1108 | 0.0308 | 0.0863 | 0.0861    | 26.59   |
| 2.3425        | 6.0   | 906  | 0.4524          | 0.109  | 0.0219 | 0.0853 | 0.087     | 31.53   |
| 0.4171        | 7.0   | 1057 | 0.4470          | 0.107  | 0.0247 | 0.0813 | 0.0825    | 26.73   |
| 0.4171        | 8.0   | 1208 | 0.4460          | 0.1129 | 0.0241 | 0.0881 | 0.0878    | 42.7    |
| 0.4171        | 9.0   | 1359 | 0.4502          | 0.0927 | 0.0224 | 0.0756 | 0.0757    | 20.47   |
| 0.3004        | 10.0  | 1510 | 0.4481          | 0.1383 | 0.0349 | 0.1114 | 0.1112    | 32.06   |
| 0.3004        | 11.0  | 1661 | 0.4501          | 0.1018 | 0.0257 | 0.083  | 0.0824    | 26.51   |
| 0.3004        | 12.0  | 1812 | 0.4563          | 0.1411 | 0.0247 | 0.112  | 0.1119    | 44.85   |
| 0.3004        | 13.0  | 1963 | 0.4567          | 0.1307 | 0.0279 | 0.1023 | 0.1028    | 34.27   |
| 0.2261        | 14.0  | 2114 | 0.4605          | 0.1253 | 0.0276 | 0.1008 | 0.0998    | 30.93   |
| 0.2261        | 15.0  | 2265 | 0.4633          | 0.1249 | 0.0279 | 0.1031 | 0.1023    | 32.43   |
| 0.2261        | 16.0  | 2416 | 0.4649          | 0.1524 | 0.0263 | 0.1208 | 0.1209    | 35.38   |
| 0.1772        | 17.0  | 2567 | 0.4664          | 0.1544 | 0.0276 | 0.1229 | 0.1225    | 41.09   |
| 0.1772        | 18.0  | 2718 | 0.4675          | 0.1496 | 0.0246 | 0.1213 | 0.1214    | 36.8    |
| 0.1772        | 19.0  | 2869 | 0.4690          | 0.1379 | 0.023  | 0.1135 | 0.1137    | 34.27   |
| 0.1548        | 20.0  | 3020 | 0.4694          | 0.1384 | 0.0233 | 0.1142 | 0.1144    | 33.01   |


### Framework versions

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