---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/bart-large-cnn
datasets:
- samsum
model-index:
- name: bart-cnn-samsum-peft
  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-cnn-samsum-peft

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4334

## 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: 1e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4513        | 1.0   | 37   | 0.5301          |
| 0.45          | 2.0   | 74   | 0.5104          |
| 0.4505        | 3.0   | 111  | 0.4969          |
| 0.4882        | 4.0   | 148  | 0.4857          |
| 0.4246        | 5.0   | 185  | 0.4759          |
| 0.386         | 6.0   | 222  | 0.4672          |
| 0.3959        | 7.0   | 259  | 0.4599          |
| 0.4179        | 8.0   | 296  | 0.4536          |
| 0.427         | 9.0   | 333  | 0.4480          |
| 0.3997        | 10.0  | 370  | 0.4435          |
| 0.4041        | 11.0  | 407  | 0.4400          |
| 0.4021        | 12.0  | 444  | 0.4371          |
| 0.3551        | 13.0  | 481  | 0.4351          |
| 0.3619        | 14.0  | 518  | 0.4338          |
| 0.3768        | 15.0  | 555  | 0.4334          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1