---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BART_reddit_other
  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_reddit_other

This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/sshleifer/distilbart-xsum-6-6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5792
- Rouge1: 18.5705
- Rouge2: 5.0107
- Rougel: 15.2581
- Rougelsum: 16.082
- Gen Len: 19.402

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.7887        | 1.0   | 1875 | 3.6044          | 18.4668 | 5.182  | 15.359  | 16.169    | 19.341  |
| 3.3816        | 2.0   | 3750 | 3.5628          | 18.0998 | 4.8937 | 15.0179 | 15.7615   | 17.789  |
| 3.134         | 3.0   | 5625 | 3.5792          | 18.5705 | 5.0107 | 15.2581 | 16.082    | 19.402  |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1