---
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: 0.3985
- Sacrebleu: 89.8136
- Rouge1: 95.6369
- Rouge2: 91.8617
- Rougel: 94.6909
- Rougelsum: 94.6811
- Bertscore Precision: 0.9424
- Bertscore Recall: 0.9374
- Bertscore F1: 0.9399

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|
| 0.1107        | 1.0   | 761  | 0.2850          | 90.5237   | 96.15   | 92.6707 | 95.2684 | 95.2821   | 0.9487              | 0.9425           | 0.9456       |
| 0.0435        | 2.0   | 1522 | 0.2695          | 91.4933   | 96.4613 | 93.4149 | 95.6712 | 95.6642   | 0.9515              | 0.9522           | 0.9518       |
| 0.0421        | 3.0   | 2283 | 0.2579          | 91.4926   | 96.4713 | 93.2669 | 95.7036 | 95.7071   | 0.9522              | 0.9505           | 0.9513       |
| 0.0233        | 4.0   | 3044 | 0.2717          | 91.8243   | 96.6369 | 93.443  | 95.8509 | 95.8593   | 0.9537              | 0.9521           | 0.9529       |
| 0.0327        | 5.0   | 3805 | 0.2804          | 92.095    | 96.6849 | 93.7485 | 95.9279 | 95.9247   | 0.9551              | 0.9526           | 0.9538       |


### Framework versions

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