---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-cnn_dailymail
  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_dailymail

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: 1.0624
- Rouge1: 24.4564
- Rouge2: 11.9696
- Rougel: 20.5207
- Rougelsum: 23.0078
- Bleu 1: 4.1113
- Bleu 2: 2.692
- Bleu 3: 1.9585
- Meteor: 12.0483
- Compression rate: 4.07

## 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: 16
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor  | Compression rate |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:------:|:------:|:------:|:-------:|:----------------:|
| 1.3117        | 1.0   | 1875  | 1.0873          | 24.4119 | 11.8902 | 20.5092 | 22.8997   | 4.1432 | 2.7081 | 1.9647 | 12.0394 | 4.0945           |
| 1.0667        | 2.0   | 3750  | 1.0588          | 24.364  | 11.9692 | 20.3498 | 22.8133   | 4.0425 | 2.6521 | 1.9328 | 11.9475 | 4.1164           |
| 0.9644        | 3.0   | 5625  | 1.0564          | 24.2853 | 11.9445 | 20.4585 | 22.8519   | 4.0533 | 2.6698 | 1.9457 | 11.9912 | 4.1173           |
| 0.8876        | 4.0   | 7500  | 1.0519          | 24.2696 | 11.8337 | 20.3562 | 22.8098   | 4.1164 | 2.698  | 1.9479 | 11.9819 | 4.0777           |
| 0.8301        | 5.0   | 9375  | 1.0556          | 24.393  | 11.9329 | 20.4502 | 22.9487   | 4.116  | 2.693  | 1.9458 | 11.9937 | 4.0738           |
| 0.7897        | 6.0   | 11250 | 1.0624          | 24.4564 | 11.9696 | 20.5207 | 23.0078   | 4.1113 | 2.692  | 1.9585 | 12.0483 | 4.07             |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1