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-1500-input-512-output
  results: []
---

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# fine-tuned-bart-20-epochs-1500-input-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: 0.4709
- Rouge1: 0.1643
- Rouge2: 0.029
- Rougel: 0.13
- Rougelsum: 0.1308
- Gen Len: 34.45

## 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  | 5.7018          | 0.1252 | 0.0051 | 0.0914 | 0.0915    | 64.16   |
| No log        | 2.0   | 302  | 0.5998          | 0.0985 | 0.0311 | 0.0875 | 0.0869    | 14.0    |
| No log        | 3.0   | 453  | 0.5101          | 0.02   | 0.0    | 0.02   | 0.02      | 8.0     |
| 3.6076        | 4.0   | 604  | 0.4777          | 0.0651 | 0.0114 | 0.052  | 0.0523    | 15.21   |
| 3.6076        | 5.0   | 755  | 0.4633          | 0.1289 | 0.032  | 0.102  | 0.1015    | 27.68   |
| 3.6076        | 6.0   | 906  | 0.4544          | 0.125  | 0.0307 | 0.0927 | 0.0919    | 42.94   |
| 0.4273        | 7.0   | 1057 | 0.4494          | 0.1197 | 0.0247 | 0.1032 | 0.1023    | 22.54   |
| 0.4273        | 8.0   | 1208 | 0.4480          | 0.1049 | 0.0252 | 0.0842 | 0.084     | 34.59   |
| 0.4273        | 9.0   | 1359 | 0.4499          | 0.088  | 0.0193 | 0.0803 | 0.0796    | 14.63   |
| 0.305         | 10.0  | 1510 | 0.4490          | 0.147  | 0.0339 | 0.1116 | 0.1114    | 44.21   |
| 0.305         | 11.0  | 1661 | 0.4524          | 0.1574 | 0.0276 | 0.1299 | 0.1283    | 31.59   |
| 0.305         | 12.0  | 1812 | 0.4538          | 0.1419 | 0.0283 | 0.1139 | 0.1136    | 30.75   |
| 0.305         | 13.0  | 1963 | 0.4577          | 0.1089 | 0.0271 | 0.0958 | 0.0948    | 21.03   |
| 0.2283        | 14.0  | 2114 | 0.4603          | 0.1348 | 0.0263 | 0.105  | 0.105     | 27.44   |
| 0.2283        | 15.0  | 2265 | 0.4651          | 0.1755 | 0.031  | 0.1368 | 0.1368    | 40.78   |
| 0.2283        | 16.0  | 2416 | 0.4667          | 0.1618 | 0.027  | 0.128  | 0.1289    | 32.36   |
| 0.1763        | 17.0  | 2567 | 0.4673          | 0.1577 | 0.0319 | 0.1238 | 0.1246    | 35.0    |
| 0.1763        | 18.0  | 2718 | 0.4682          | 0.1655 | 0.0317 | 0.132  | 0.1328    | 38.98   |
| 0.1763        | 19.0  | 2869 | 0.4699          | 0.161  | 0.0289 | 0.1294 | 0.1307    | 37.17   |
| 0.1504        | 20.0  | 3020 | 0.4709          | 0.1643 | 0.029  | 0.13   | 0.1308    | 34.45   |


### Framework versions

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