transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:facebook/bart-base base_model:finetune:facebook/bart-base license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/bart-base
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart-base_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-base_readme_summarization

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8669
- Rouge1: 0.5127
- Rouge2: 0.3646
- Rougel: 0.4876
- Rougelsum: 0.4869
- Gen Len: 14.0839

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5281        | 1.0   | 1458 | 2.1087          | 0.4819 | 0.3345 | 0.4579 | 0.4568    | 14.0504 |
| 2.0703        | 2.0   | 2916 | 1.9665          | 0.4965 | 0.3464 | 0.4732 | 0.472     | 13.3129 |
| 1.7808        | 3.0   | 4374 | 1.9068          | 0.5065 | 0.3557 | 0.4815 | 0.4811    | 14.271  |
| 1.604         | 4.0   | 5832 | 1.8722          | 0.5082 | 0.3634 | 0.4878 | 0.4873    | 13.8849 |
| 1.5412        | 5.0   | 7290 | 1.8669          | 0.5127 | 0.3646 | 0.4876 | 0.4869    | 14.0839 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
