---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-roundup-2-8
  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-2-8

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: 1.1855
- Rouge1: 53.552
- Rouge2: 34.9077
- Rougel: 38.0158
- Rougelsum: 50.7179
- 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   | 167  | 1.2085          | 50.8706 | 32.0069 | 32.9241 | 47.9805   | 142.0    |
| No log        | 2.0   | 334  | 1.0897          | 53.2218 | 34.1317 | 34.4827 | 50.4795   | 139.4286 |
| 1.0256        | 3.0   | 501  | 1.0535          | 50.8882 | 30.2514 | 31.5051 | 47.9856   | 141.9048 |
| 1.0256        | 4.0   | 668  | 1.0515          | 54.9414 | 35.2309 | 36.006  | 52.0331   | 142.0    |
| 1.0256        | 5.0   | 835  | 1.0829          | 53.0709 | 33.4587 | 36.4223 | 50.1627   | 140.7619 |
| 0.4579        | 6.0   | 1002 | 1.1310          | 51.5274 | 30.7069 | 32.4146 | 48.8851   | 142.0    |
| 0.4579        | 7.0   | 1169 | 1.1670          | 52.1536 | 31.7158 | 35.7483 | 49.2678   | 142.0    |
| 0.4579        | 8.0   | 1336 | 1.1855          | 53.552  | 34.9077 | 38.0158 | 50.7179   | 142.0    |


### Framework versions

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