---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: bart-samsum-finetuned
  results: []
metrics:
- bertscore
- bleu
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bart-samsum-finetuned

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1326

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1196        | 1.0   | 74   | 0.1362          |
| 0.0948        | 2.0   | 148  | 0.1334          |
| 0.0738        | 3.0   | 222  | 0.1326          |

### Evaluation results

Rouge Scores:

| Metric     |     Precision     |       Recall      |       F-Measure      |
|:----------:|:-----------------:|:-----------------:|:--------------------:|
| rouge1     |  Low -  0.2923    |   Low -  0.5755   |    Low -  0.3645     |
|            |  Mid -  0.3012    |   Mid -  0.5881   |    Mid -  0.3722     |
|            |  High - 0.3108    |   High - 0.6011   |    High - 0.3811     |
| rouge2     |  Low -  0.1185    |   Low -  0.2418   |    Low -  0.1481     |
|            |  Mid -  0.1252    |   Mid -  0.2545   |    Mid -  0.1555     |
|            |  High - 0.1321    |   High - 0.2682   |    High - 0.1632     |
| rougeL     |  Low -  0.2182    |   Low -  0.4434   |    Low -  0.2744     |
|            |  Mid -  0.2251    |   Mid -  0.4547   |    Mid -  0.2810     |
|            |  High - 0.2328    |   High - 0.4679   |    High - 0.2886     |
| rougeLsum  |  Low -  0.2178    |   Low -  0.4425   |    Low -  0.2739     |
|            |  Mid -  0.2249    |   Mid -  0.4546   |    Mid -  0.2807     |
|            |  High - 0.2321    |   High -  0.4679  |    High - 0.2883     |


BERTScore:

| Precision |   Recall  |     F1    |
|:---------:|:---------:|:---------:|
| 0.6054495 | 0.6918860 | 0.6425597 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2