---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: bart-base-cnndm
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: test
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 25.0336
---

<!-- 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-base-cnndm

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5802
- Rouge1: 25.0336
- Rouge2: 12.5344
- Rougel: 20.8721
- Rougelsum: 23.5806
- Gen Len: 19.9998

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.845         | 1.0   | 8972  | 1.6461          | 24.8325 | 12.327  | 20.6952 | 23.3653   | 19.9998 |
| 1.7427        | 2.0   | 17945 | 1.6098          | 24.9118 | 12.4577 | 20.786  | 23.4624   | 19.9998 |
| 1.6727        | 3.0   | 26917 | 1.5881          | 24.9723 | 12.4738 | 20.8317 | 23.5195   | 19.9994 |
| 1.6288        | 4.0   | 35888 | 1.5802          | 25.0336 | 12.5344 | 20.8721 | 23.5806   | 19.9998 |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.1+cu118
- Datasets 2.9.0
- Tokenizers 0.13.3