---
language:
- sv-SE
license: cc0-1.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
  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. -->

# 

This model is a fine-tuned version of [marinone94/xls-r-300m-sv-robust](https://huggingface.co/marinone94/xls-r-300m-sv-robust) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SV-SE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1497
- Wer: 0.1261

## 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: 0.00025
- 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_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.3533        | 1.1   | 100  | 3.2807          | 1.0    |
| 3.1709        | 2.2   | 200  | 3.1325          | 1.0    |
| 3.0573        | 3.3   | 300  | 3.0615          | 1.0    |
| 3.0314        | 4.39  | 400  | 3.0990          | 1.0    |
| 3.0129        | 5.49  | 500  | 3.0400          | 1.0    |
| 2.9964        | 6.59  | 600  | 2.9990          | 1.0    |
| 2.9602        | 7.69  | 700  | 2.9620          | 1.0    |
| 2.8756        | 8.79  | 800  | 2.7302          | 1.0    |
| 2.2931        | 9.89  | 900  | 1.5058          | 0.9776 |
| 1.8427        | 10.98 | 1000 | 0.9155          | 0.7832 |
| 1.4286        | 12.09 | 1100 | 0.4075          | 0.3796 |
| 1.2229        | 13.19 | 1200 | 0.2893          | 0.2652 |
| 1.1106        | 14.28 | 1300 | 0.2469          | 0.2254 |
| 1.0663        | 15.38 | 1400 | 0.2219          | 0.1973 |
| 1.0667        | 16.48 | 1500 | 0.2129          | 0.1894 |
| 1.0193        | 17.58 | 1600 | 0.1991          | 0.1789 |
| 0.9816        | 18.68 | 1700 | 0.1940          | 0.1801 |
| 0.9814        | 19.78 | 1800 | 0.1860          | 0.1667 |
| 0.9787        | 20.87 | 1900 | 0.1888          | 0.1642 |
| 0.9699        | 21.97 | 2000 | 0.1875          | 0.1704 |
| 0.9616        | 23.08 | 2100 | 0.1802          | 0.1617 |
| 0.9378        | 24.17 | 2200 | 0.1793          | 0.1577 |
| 0.888         | 25.27 | 2300 | 0.1764          | 0.1545 |
| 0.8942        | 26.37 | 2400 | 0.1674          | 0.1492 |
| 0.8701        | 27.47 | 2500 | 0.1739          | 0.1512 |
| 0.8555        | 28.57 | 2600 | 0.1690          | 0.1446 |
| 0.8513        | 29.67 | 2700 | 0.1649          | 0.1477 |
| 0.8659        | 30.77 | 2800 | 0.1637          | 0.1422 |
| 0.8419        | 31.86 | 2900 | 0.1614          | 0.1397 |
| 0.8491        | 32.96 | 3000 | 0.1595          | 0.1401 |
| 0.8395        | 34.07 | 3100 | 0.1607          | 0.1376 |
| 0.83          | 35.16 | 3200 | 0.1538          | 0.1379 |
| 0.7835        | 36.26 | 3300 | 0.1602          | 0.1408 |
| 0.7703        | 37.36 | 3400 | 0.1601          | 0.1369 |
| 0.7474        | 38.46 | 3500 | 0.1514          | 0.1342 |
| 0.7719        | 39.56 | 3600 | 0.1593          | 0.1353 |
| 0.7638        | 40.66 | 3700 | 0.1536          | 0.1338 |
| 0.771         | 41.75 | 3800 | 0.1531          | 0.1317 |
| 0.7594        | 42.85 | 3900 | 0.1498          | 0.1288 |
| 0.7383        | 43.95 | 4000 | 0.1527          | 0.1300 |
| 0.7565        | 45.05 | 4100 | 0.1482          | 0.1289 |
| 0.7697        | 46.15 | 4200 | 0.1495          | 0.1272 |
| 0.7194        | 47.25 | 4300 | 0.1493          | 0.1269 |
| 0.7479        | 48.35 | 4400 | 0.1490          | 0.1276 |
| 0.7132        | 49.45 | 4500 | 0.1501          | 0.1265 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0