---
language:
- sv
license: cc0-1.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_9_0
- generated_from_trainer
- sv
datasets:
- mozilla-foundation/common_voice_9_0
model-index:
- name: XLS-R-300M - Swedish
  results:
  - task: 
      name: Automatic Speech Recognition 
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_9_0
      type: mozilla-foundation/common_voice_9_0
      split: test
      args: sv-SE
      WER: 
    metrics:
       - name: Test WER
         type: wer
         value: 7.72
       - name: Test CER
         type: cer
         value: 2.61
  - task: 
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: speech-recognition-community-v2/dev_data
      type: speech-recognition-community-v2/dev_data
      split: validation
      args: sv
    metrics:
       - name: Test WER
         type: wer
         value: 16.23
       - name: Test CER
         type: cer
         value: 8.21
  - task: 
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: speech-recognition-community-v2/dev_data
      type: speech-recognition-community-v2/dev_data
      split: test
      args: sv
    metrics:
       - name: Test WER
         type: wer
         value: 15.08
       - name: Test CER
         type: cer
         value: 7.51
---
# 

This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - SV-SE dataset.
It achieves the following results on the evaluation set ("test" split, without LM):
- Loss: 0.1318
- Wer: 0.1121

## 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: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9099        | 10.42 | 1000 | 2.8369          | 1.0    |
| 1.0745        | 20.83 | 2000 | 0.1957          | 0.1673 |
| 0.934         | 31.25 | 3000 | 0.1579          | 0.1389 |
| 0.8691        | 41.66 | 4000 | 0.1457          | 0.1290 |
| 0.8328        | 52.08 | 5000 | 0.1435          | 0.1205 |
| 0.8068        | 62.5  | 6000 | 0.1350          | 0.1191 |
| 0.7822        | 72.91 | 7000 | 0.1347          | 0.1155 |
| 0.7769        | 83.33 | 8000 | 0.1321          | 0.1131 |
| 0.7678        | 93.75 | 9000 | 0.1321          | 0.1115 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.11.0