---
license: mit
base_model: facebook/bart-large-cnn
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-samsum
  results: []
---

<!-- 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-large-samsum

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3635
- Rouge1: 0.3962
- Rouge2: 0.2011
- Rougel: 0.3064
- Rougelsum: 0.3064

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.3824        | 0.43  | 400  | 1.4666          | 0.3995 | 0.2014 | 0.3061 | 0.3064    |
| 1.2617        | 0.87  | 800  | 1.3350          | 0.4065 | 0.2063 | 0.3113 | 0.3115    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2