---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-cnn-xsum-swe
  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-base-cnn-xsum-swe

This model is a fine-tuned version of [Gabriel/bart-base-cnn-swe](https://huggingface.co/Gabriel/bart-base-cnn-swe) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1140
- Rouge1: 30.7101
- Rouge2: 11.9532
- Rougel: 25.1864
- Rougelsum: 25.2227
- Gen Len: 19.7448

## 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: 3.75e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.3087        | 1.0   | 6375  | 2.1997          | 29.7666 | 11.0222 | 24.2659 | 24.2915   | 19.7172 |
| 2.0793        | 2.0   | 12750 | 2.1285          | 30.4447 | 11.7671 | 24.9238 | 24.9622   | 19.7051 |
| 1.9186        | 3.0   | 19125 | 2.1140          | 30.7101 | 11.9532 | 25.1864 | 25.2227   | 19.7448 |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1