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-wanglab-512-output
  results: []
---

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# fine-tuned-BART-20-epochs-wanglab-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: 0.4945
- Rouge1: 0.0871
- Rouge2: 0.0196
- Rougel: 0.0787
- Rougelsum: 0.0787
- Bertscore F1: 0.837
- Bleurt Score: -1.873
- Gen Len: 20.0

## 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: 4
- eval_batch_size: 4
- 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 | Bertscore F1 | Bleurt Score | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------------:|:------------:|:-------:|
| No log        | 1.0   | 301  | 1.5515          | 0.0293 | 0.0    | 0.0286 | 0.0282    | 0.7994       | -2.1159      | 11.68   |
| 4.8736        | 2.0   | 602  | 0.5364          | 0.0738 | 0.0183 | 0.0655 | 0.0653    | 0.8345       | -1.6735      | 20.0    |
| 4.8736        | 3.0   | 903  | 0.4811          | 0.071  | 0.0191 | 0.0677 | 0.0677    | 0.8359       | -1.7563      | 20.0    |
| 0.5377        | 4.0   | 1204 | 0.4621          | 0.0506 | 0.0125 | 0.0475 | 0.0474    | 0.8566       | -1.8275      | 8.0     |
| 0.4145        | 5.0   | 1505 | 0.4496          | 0.0231 | 0.0036 | 0.0237 | 0.0233    | 0.8458       | -1.4636      | 8.0     |
| 0.4145        | 6.0   | 1806 | 0.4455          | 0.078  | 0.0194 | 0.0714 | 0.071     | 0.8469       | -1.3815      | 20.0    |
| 0.336         | 7.0   | 2107 | 0.4416          | 0.0871 | 0.0196 | 0.0787 | 0.0787    | 0.837        | -1.873       | 20.0    |
| 0.336         | 8.0   | 2408 | 0.4440          | 0.0878 | 0.0195 | 0.0794 | 0.0791    | 0.8409       | -1.4561      | 20.0    |
| 0.2698        | 9.0   | 2709 | 0.4505          | 0.0231 | 0.0036 | 0.0237 | 0.0233    | 0.8458       | -1.4636      | 8.0     |
| 0.2225        | 10.0  | 3010 | 0.4546          | 0.0516 | 0.0101 | 0.0466 | 0.0463    | 0.8355       | -1.61        | 20.0    |
| 0.2225        | 11.0  | 3311 | 0.4627          | 0.0877 | 0.0194 | 0.0794 | 0.0791    | 0.8388       | -1.4342      | 20.0    |
| 0.1695        | 12.0  | 3612 | 0.4677          | 0.0704 | 0.0128 | 0.0628 | 0.0626    | 0.8218       | -1.8469      | 20.0    |
| 0.1695        | 13.0  | 3913 | 0.4716          | 0.0615 | 0.0193 | 0.056  | 0.0557    | 0.8342       | -1.5375      | 20.0    |
| 0.132         | 14.0  | 4214 | 0.4754          | 0.064  | 0.0196 | 0.0577 | 0.0576    | 0.839        | -1.8751      | 20.0    |
| 0.1122        | 15.0  | 4515 | 0.4837          | 0.0712 | 0.0175 | 0.0644 | 0.0642    | 0.8373       | -1.3366      | 20.0    |
| 0.1122        | 16.0  | 4816 | 0.4867          | 0.0817 | 0.01   | 0.0691 | 0.069     | 0.8425       | -1.4584      | 20.0    |
| 0.0893        | 17.0  | 5117 | 0.4904          | 0.0712 | 0.0175 | 0.0644 | 0.0642    | 0.8373       | -1.3366      | 20.0    |
| 0.0893        | 18.0  | 5418 | 0.4924          | 0.0871 | 0.0196 | 0.0787 | 0.0787    | 0.837        | -1.873       | 20.0    |
| 0.08          | 19.0  | 5719 | 0.4934          | 0.0871 | 0.0196 | 0.0787 | 0.0787    | 0.837        | -1.873       | 20.0    |
| 0.0706        | 20.0  | 6020 | 0.4945          | 0.0871 | 0.0196 | 0.0787 | 0.0787    | 0.837        | -1.873       | 20.0    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
