---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
model-index:
- name: Bart
  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

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4379

## 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: 2e-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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 32   | 1.9039          |
| No log        | 2.0   | 64   | 1.9118          |
| No log        | 3.0   | 96   | 1.9611          |
| No log        | 4.0   | 128  | 2.1126          |
| No log        | 5.0   | 160  | 2.3234          |
| No log        | 6.0   | 192  | 2.5468          |
| No log        | 7.0   | 224  | 2.6987          |
| No log        | 8.0   | 256  | 2.8041          |
| No log        | 9.0   | 288  | 2.9329          |
| No log        | 10.0  | 320  | 3.0530          |
| No log        | 11.0  | 352  | 3.1344          |
| No log        | 12.0  | 384  | 3.1571          |
| No log        | 13.0  | 416  | 3.2308          |
| No log        | 14.0  | 448  | 3.3060          |
| No log        | 15.0  | 480  | 3.3254          |
| 0.55          | 16.0  | 512  | 3.3449          |
| 0.55          | 17.0  | 544  | 3.3627          |
| 0.55          | 18.0  | 576  | 3.4195          |
| 0.55          | 19.0  | 608  | 3.4282          |
| 0.55          | 20.0  | 640  | 3.4379          |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1