---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-roundup-3-8
  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-3-8

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: 1.4132
- Rouge1: 49.6606
- Rouge2: 28.4044
- Rougel: 31.5419
- Rougelsum: 46.2463
- 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   | 258  | 1.2686          | 48.8513 | 28.7007 | 31.1199 | 45.7318   | 142.0    |
| 1.1738        | 2.0   | 516  | 1.1884          | 49.8072 | 28.9817 | 31.3611 | 46.9639   | 141.6875 |
| 1.1738        | 3.0   | 774  | 1.1970          | 49.3865 | 28.3426 | 30.0945 | 46.4681   | 141.3438 |
| 0.7069        | 4.0   | 1032 | 1.1984          | 50.6743 | 29.4728 | 31.5364 | 47.989    | 141.7188 |
| 0.7069        | 5.0   | 1290 | 1.2494          | 49.4461 | 28.9295 | 31.0334 | 46.6611   | 142.0    |
| 0.4618        | 6.0   | 1548 | 1.2954          | 50.6789 | 30.2783 | 32.1932 | 47.5929   | 142.0    |
| 0.4618        | 7.0   | 1806 | 1.3638          | 49.9476 | 30.223  | 32.4346 | 46.7383   | 142.0    |
| 0.3293        | 8.0   | 2064 | 1.4132          | 49.6606 | 28.4044 | 31.5419 | 46.2463   | 142.0    |


### Framework versions

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