transformers safetensors bart text2text-generation generated_from_trainer base_model:facebook/bart-large-xsum base_model:finetune:facebook/bart-large-xsum license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/bart-large-xsum
license: mit
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart-large-xsum_readme_summarization
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bart-large-xsum_readme_summarization

This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1218
- Rouge1: 0.5637
- Rouge2: 0.4319
- Rougel: 0.5369
- Rougelsum: 0.5371
- Gen Len: 21.5048

## 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: 2e-05
- 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
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.1078        | 1.0   | 1458 | 1.9876          | 0.4994 | 0.3426 | 0.4684 | 0.4682    | 20.1103 |
| 1.3919        | 2.0   | 2916 | 1.8539          | 0.5137 | 0.3697 | 0.4841 | 0.4839    | 21.8345 |
| 0.9878        | 3.0   | 4374 | 1.9027          | 0.5441 | 0.401  | 0.5174 | 0.5171    | 20.1487 |
| 0.6594        | 4.0   | 5832 | 2.0362          | 0.5628 | 0.4272 | 0.5385 | 0.538     | 21.3417 |
| 0.4691        | 5.0   | 7290 | 2.1218          | 0.5637 | 0.4319 | 0.5369 | 0.5371    | 21.5048 |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
