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

# amb-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: 0.8578
- Rouge1: 0.6039
- Rouge2: 0.3487
- Rougel: 0.4805
- Rougelsum: 0.4805
- Gen Len: 101.0

## 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    | 1.1889          | 0.5926 | 0.2701 | 0.3828 | 0.3828    | 65.5    |
| No log        | 2.0   | 2    | 1.0179          | 0.6489 | 0.3333 | 0.458  | 0.458     | 77.5    |
| No log        | 3.0   | 3    | 0.9405          | 0.6084 | 0.2627 | 0.3783 | 0.3783    | 82.5    |
| No log        | 4.0   | 4    | 0.8990          | 0.6241 | 0.3058 | 0.4054 | 0.4054    | 86.0    |
| No log        | 5.0   | 5    | 0.8814          | 0.6746 | 0.3882 | 0.4842 | 0.4842    | 95.0    |
| No log        | 6.0   | 6    | 0.8679          | 0.5554 | 0.3111 | 0.4127 | 0.4127    | 94.5    |
| No log        | 7.0   | 7    | 0.8607          | 0.5799 | 0.3016 | 0.4153 | 0.4153    | 100.0   |
| No log        | 8.0   | 8    | 0.8578          | 0.6039 | 0.3487 | 0.4805 | 0.4805    | 101.0   |


### Framework versions

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