---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-sec
  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. -->

# distilbart-cnn-12-6-sec

This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co./sshleifer/distilbart-cnn-12-6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0798
- Rouge1: 72.1665
- Rouge2: 62.2601
- Rougel: 67.8376
- Rougelsum: 71.1407
- Gen Len: 121.62

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 99   | 0.3526          | 53.3978 | 38.6395 | 45.6271 | 51.0477   | 111.48  |
| No log        | 2.0   | 198  | 0.1961          | 55.7397 | 43.6293 | 50.9595 | 54.0764   | 111.46  |
| No log        | 3.0   | 297  | 0.1483          | 66.9443 | 54.8966 | 62.6678 | 65.6787   | 118.64  |
| No log        | 4.0   | 396  | 0.1218          | 67.2661 | 56.1852 | 63.1339 | 65.8066   | 124.92  |
| No log        | 5.0   | 495  | 0.1139          | 67.2097 | 55.8694 | 62.7508 | 65.9706   | 123.02  |
| 0.4156        | 6.0   | 594  | 0.0940          | 71.607  | 60.6697 | 66.7873 | 70.339    | 122.84  |
| 0.4156        | 7.0   | 693  | 0.0888          | 71.3792 | 61.8326 | 68.25   | 70.5113   | 124.4   |
| 0.4156        | 8.0   | 792  | 0.0870          | 72.7472 | 62.6968 | 68.2853 | 71.5789   | 124.34  |
| 0.4156        | 9.0   | 891  | 0.0799          | 73.4438 | 63.5966 | 68.8737 | 72.3014   | 119.88  |
| 0.4156        | 10.0  | 990  | 0.0798          | 72.1665 | 62.2601 | 67.8376 | 71.1407   | 121.62  |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1