---
base_model: smazhug2024/bart-cnn-samsum-finetuned
datasets:
- samsum
library_name: peft
license: mit
tags:
- generated_from_trainer
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 [smazhug2024/bart-cnn-samsum-finetuned](https://huggingface.co./smazhug2024/bart-cnn-samsum-finetuned) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1361

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0918        | 1.0   | 19   | 0.1363          |
| 0.0959        | 2.0   | 38   | 0.1362          |
| 0.0916        | 3.0   | 57   | 0.1361          |
| 0.0878        | 4.0   | 76   | 0.1361          |
| 0.1026        | 5.0   | 95   | 0.1361          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1