---
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summary-tragedy-Bart-Large-CNN
  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. -->

# summary-tragedy-Bart-Large-CNN

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: 2.4758
- Rouge1: 0.3972
- Rouge2: 0.1525
- Rougel: 0.2279
- Rougelsum: 0.2297
- Gen Len: 142.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.8064        | 1.0   | 10   | 2.5907          | 0.3676 | 0.08   | 0.1808 | 0.1804    | 136.0   |
| 2.4065        | 2.0   | 20   | 2.5102          | 0.3116 | 0.0669 | 0.1732 | 0.1732    | 142.0   |
| 2.2329        | 3.0   | 30   | 2.4821          | 0.3931 | 0.108  | 0.2077 | 0.2074    | 142.0   |
| 2.1376        | 4.0   | 40   | 2.4786          | 0.3972 | 0.1525 | 0.2279 | 0.2297    | 142.0   |
| 2.0733        | 5.0   | 50   | 2.4758          | 0.3972 | 0.1525 | 0.2279 | 0.2297    | 142.0   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3