---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xlsr-128upper-sorbian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: hsb
      split: validation
      args: hsb
    metrics:
    - name: Wer
      type: wer
      value: 0.5044303797468355
---

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# xlsr-128upper-sorbian

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7625
- Wer: 0.5044
- Cer: 0.1106

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 3.8489        | 3.9216  | 100  | 4.0479          | 1.0    | 1.0    |
| 3.1996        | 7.8431  | 200  | 3.2124          | 0.9804 | 0.9850 |
| 2.3527        | 11.7647 | 300  | 2.4026          | 1.0    | 0.6858 |
| 0.4424        | 15.6863 | 400  | 0.7917          | 0.7418 | 0.1910 |
| 0.2617        | 19.6078 | 500  | 0.7624          | 0.6804 | 0.1696 |
| 0.1421        | 23.5294 | 600  | 0.7839          | 0.6582 | 0.1579 |
| 0.097         | 27.4510 | 700  | 0.8322          | 0.6316 | 0.1495 |
| 0.0459        | 31.3725 | 800  | 0.8119          | 0.6171 | 0.1446 |
| 0.0668        | 35.2941 | 900  | 0.8534          | 0.6418 | 0.1535 |
| 0.0627        | 39.2157 | 1000 | 0.8256          | 0.6019 | 0.1397 |
| 0.0454        | 43.1373 | 1100 | 0.7747          | 0.5994 | 0.1363 |
| 0.04          | 47.0588 | 1200 | 0.8046          | 0.5810 | 0.1321 |
| 0.0563        | 50.9804 | 1300 | 0.7910          | 0.5797 | 0.1325 |
| 0.039         | 54.9020 | 1400 | 0.7370          | 0.5595 | 0.1265 |
| 0.0254        | 58.8235 | 1500 | 0.7395          | 0.5418 | 0.1188 |
| 0.0211        | 62.7451 | 1600 | 0.7582          | 0.5430 | 0.1209 |
| 0.0218        | 66.6667 | 1700 | 0.7123          | 0.5051 | 0.1121 |
| 0.0206        | 70.5882 | 1800 | 0.7912          | 0.5297 | 0.1165 |
| 0.0155        | 74.5098 | 1900 | 0.7671          | 0.5367 | 0.1183 |
| 0.0242        | 78.4314 | 2000 | 0.7926          | 0.5418 | 0.1170 |
| 0.0081        | 82.3529 | 2100 | 0.7817          | 0.5373 | 0.1221 |
| 0.0087        | 86.2745 | 2200 | 0.7989          | 0.5285 | 0.1165 |
| 0.0088        | 90.1961 | 2300 | 0.7523          | 0.5165 | 0.1141 |
| 0.0173        | 94.1176 | 2400 | 0.7646          | 0.5038 | 0.1108 |
| 0.0217        | 98.0392 | 2500 | 0.7625          | 0.5044 | 0.1106 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1