---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-roundup-4-8
  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-large-cnn-finetuned-roundup-4-8

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7790
- Rouge1: 54.3036
- Rouge2: 37.1443
- Rougel: 40.4762
- Rougelsum: 52.1796
- 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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   | 398  | 0.9580          | 52.5184 | 33.0208 | 35.0634 | 49.9083   | 142.0    |
| 1.119         | 2.0   | 796  | 0.8356          | 53.0801 | 34.5549 | 36.9807 | 50.3394   | 141.2963 |
| 0.6814        | 3.0   | 1194 | 0.7968          | 53.9433 | 34.8086 | 36.7654 | 51.3384   | 142.0    |
| 0.4623        | 4.0   | 1592 | 0.7474          | 53.947  | 36.2662 | 39.332  | 51.7559   | 142.0    |
| 0.4623        | 5.0   | 1990 | 0.7563          | 54.5816 | 37.0675 | 40.3592 | 52.2391   | 142.0    |
| 0.3228        | 6.0   | 2388 | 0.7383          | 54.787  | 37.3647 | 40.521  | 52.3113   | 142.0    |
| 0.2183        | 7.0   | 2786 | 0.7606          | 54.1822 | 37.6748 | 40.7956 | 52.1102   | 141.7778 |
| 0.1759        | 8.0   | 3184 | 0.7790          | 54.3036 | 37.1443 | 40.4762 | 52.1796   | 142.0    |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1