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

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: 1.8594
- Rouge1: 0.1876
- Rouge2: 0.1056
- Rougel: 0.1659
- Rougelsum: 0.1757

## 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: 5.6e-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
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.6078        | 1.0   | 63   | 1.9681          | 0.1706 | 0.0988 | 0.1529 | 0.1607    |
| 2.0494        | 2.0   | 126  | 1.8818          | 0.1908 | 0.1085 | 0.17   | 0.1792    |
| 1.8102        | 3.0   | 189  | 1.8500          | 0.1888 | 0.1084 | 0.1665 | 0.175     |
| 1.627         | 4.0   | 252  | 1.8500          | 0.185  | 0.1033 | 0.1631 | 0.1718    |
| 1.4668        | 5.0   | 315  | 1.8453          | 0.1793 | 0.1072 | 0.1612 | 0.1689    |
| 1.3781        | 6.0   | 378  | 1.8412          | 0.1815 | 0.1018 | 0.159  | 0.1697    |
| 1.292         | 7.0   | 441  | 1.8545          | 0.1868 | 0.1067 | 0.1667 | 0.175     |
| 1.253         | 8.0   | 504  | 1.8594          | 0.1876 | 0.1056 | 0.1659 | 0.1757    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
