---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
model-index:
- name: bart-cnndm
  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-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: 1.6305

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0521        | 0.06  | 500  | 1.8483          |
| 2.0187        | 0.11  | 1000 | 1.7939          |
| 1.9884        | 0.17  | 1500 | 1.7849          |
| 2.0118        | 0.22  | 2000 | 1.7372          |
| 1.9341        | 0.28  | 2500 | 1.7180          |
| 1.8866        | 0.33  | 3000 | 1.7186          |
| 1.9491        | 0.39  | 3500 | 1.6971          |
| 1.8668        | 0.45  | 4000 | 1.6930          |
| 1.9666        | 0.5   | 4500 | 1.6570          |
| 1.9386        | 0.56  | 5000 | 1.6703          |
| 1.9207        | 0.61  | 5500 | 1.6570          |
| 1.876         | 0.67  | 6000 | 1.6571          |
| 1.9118        | 0.72  | 6500 | 1.6541          |
| 1.8098        | 0.78  | 7000 | 1.6506          |
| 1.8564        | 0.84  | 7500 | 1.6391          |
| 1.8527        | 0.89  | 8000 | 1.6376          |
| 1.7987        | 0.95  | 8500 | 1.6324          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2