---
language: sv
license: mit
metrics:
- rouge
model-index:
- name: bart-base-cnn-swe
  results:
    - task: 
        type: summarization
        name: summarization
      dataset:
        name: Gabriel/cnn_daily_swe
        type: Gabriel/cnn_daily_swe
        split: validation
      metrics:
           - name: Validation ROGUE-1
             type: rouge-1
             value: 21.7291
             verified: true
           - name: Validation ROGUE-2
             type: rouge-2
             value: 10.0209
             verified: true
           - name: Validation ROGUE-L
             type: rouge-l
             value: 17.775
             verified: true
 
datasets:
- Gabriel/cnn_daily_swe
tags:
- summarization

widget:
-text: "Minst två personer dödades i en misstänkt bomb attack på en personbuss i de stridiga södra filippiner på måndag, sade militären."
---

# bart-base-cnn-swe

This model is a fine-tuned version of [KBLab/bart-base-swedish-cased](https://huggingface.co/KBLab/bart-base-swedish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1656
- Rouge1: 21.7291
- Rouge2: 10.0209
- Rougel: 17.775
- Rougelsum: 20.429
- Gen Len: 19.9931

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:------:|:---------:|:-------:|
| 2.3512        | 1.0   | 17944 | 2.1656          | 21.7291 | 10.0209 | 17.775 | 20.429    | 19.9931 |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1