---
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: small-dataset-factor
  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. -->

# small-dataset-factor

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: 1.0342
- Rouge1: 0.7004
- Rouge2: 0.5624
- Rougel: 0.5489
- Rougelsum: 0.5489
- Gen Len: 72.0

## 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: 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 1    | 1.4501          | 0.5989 | 0.3974 | 0.493  | 0.493     | 61.5    |
| No log        | 2.0   | 2    | 1.4501          | 0.5989 | 0.3974 | 0.493  | 0.493     | 61.5    |
| No log        | 3.0   | 3    | 1.2372          | 0.6418 | 0.459  | 0.5287 | 0.5287    | 66.5    |
| No log        | 4.0   | 4    | 1.1366          | 0.6293 | 0.4495 | 0.5183 | 0.5183    | 68.0    |
| No log        | 5.0   | 5    | 1.0768          | 0.6763 | 0.5432 | 0.5941 | 0.5941    | 75.0    |
| No log        | 6.0   | 6    | 1.0550          | 0.6846 | 0.5503 | 0.5357 | 0.5357    | 74.0    |
| No log        | 7.0   | 7    | 1.0425          | 0.6846 | 0.5503 | 0.5357 | 0.5357    | 74.0    |
| No log        | 8.0   | 8    | 1.0342          | 0.7004 | 0.5624 | 0.5489 | 0.5489    | 72.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1