---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- sacrebleu
- rouge
model-index:
- name: bart-base-finetuned-w-data-augm-4e-5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bart-base-finetuned-w-data-augm-4e-5

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: 0.3874
- Sacrebleu: 89.8161
- Rouge1: 95.6774
- Rouge2: 91.8937
- Rougel: 94.6649
- Rougelsum: 94.6595
- Bertscore Precision: 0.9414
- Bertscore Recall: 0.9376
- Bertscore F1: 0.9395

## 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: 4.4252514647201465e-05
- train_batch_size: 16
- eval_batch_size: 32
- 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 | Sacrebleu | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|
| 0.1504        | 1.0   | 761  | 0.2797          | 90.9313   | 96.2421 | 92.8783 | 95.4262 | 95.4043   | 0.9496              | 0.9444           | 0.9469       |
| 0.0348        | 2.0   | 1522 | 0.2473          | 91.7583   | 96.3865 | 93.2655 | 95.6899 | 95.6811   | 0.9532              | 0.9504           | 0.9517       |
| 0.0587        | 3.0   | 2283 | 0.2413          | 91.828    | 96.4392 | 93.4124 | 95.7079 | 95.6976   | 0.9517              | 0.9508           | 0.9512       |
| 0.0269        | 4.0   | 3044 | 0.2588          | 91.9835   | 96.578  | 93.6221 | 95.8992 | 95.8798   | 0.9524              | 0.9527           | 0.9525       |
| 0.0439        | 5.0   | 3805 | 0.2678          | 92.1033   | 96.6815 | 93.6391 | 95.9677 | 95.9469   | 0.9544              | 0.9536           | 0.954        |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1