---
base_model: facebook/bart-large-cnn
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: fine_tuned_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. -->

# fine_tuned_bart

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7075

## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 8    | 0.7205          |
| 0.4729        | 2.0   | 16   | 0.7109          |
| 0.4794        | 3.0   | 24   | 0.7048          |
| 0.4716        | 4.0   | 32   | 0.7081          |
| 0.476         | 5.0   | 40   | 0.7095          |
| 0.476         | 6.0   | 48   | 0.7174          |
| 0.4751        | 7.0   | 56   | 0.7050          |
| 0.4683        | 8.0   | 64   | 0.7047          |
| 0.4583        | 9.0   | 72   | 0.7058          |
| 0.474         | 10.0  | 80   | 0.7045          |
| 0.474         | 11.0  | 88   | 0.7062          |
| 0.4651        | 12.0  | 96   | 0.7047          |
| 0.4523        | 13.0  | 104  | 0.7028          |
| 0.4626        | 14.0  | 112  | 0.7049          |
| 0.4634        | 15.0  | 120  | 0.7067          |
| 0.4634        | 16.0  | 128  | 0.7091          |
| 0.4543        | 17.0  | 136  | 0.7087          |
| 0.4502        | 18.0  | 144  | 0.7084          |
| 0.4604        | 19.0  | 152  | 0.7098          |
| 0.4503        | 20.0  | 160  | 0.7065          |
| 0.4503        | 21.0  | 168  | 0.7046          |
| 0.4642        | 22.0  | 176  | 0.7033          |
| 0.4334        | 23.0  | 184  | 0.7029          |
| 0.4626        | 24.0  | 192  | 0.7037          |
| 0.4584        | 25.0  | 200  | 0.7046          |
| 0.4584        | 26.0  | 208  | 0.7063          |
| 0.4508        | 27.0  | 216  | 0.7075          |
| 0.4498        | 28.0  | 224  | 0.7078          |
| 0.4532        | 29.0  | 232  | 0.7077          |
| 0.4514        | 30.0  | 240  | 0.7075          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1