pytorch tensorboard wav2vec2 automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
  name: wav2vec2-xlsr-vorarlbergerisch
---

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# wav2vec2-xlsr-vorarlbergerisch

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-german](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-german) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3193
- Wer: 0.3235

## 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: 62
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 15.6717       | 3.83  | 100  | 3.0247          | 1.0    |
| 2.485         | 7.68  | 200  | 1.5937          | 0.9046 |
| 0.784         | 11.53 | 300  | 1.2664          | 0.5    |
| 0.3689        | 15.38 | 400  | 1.2046          | 0.4696 |
| 0.2618        | 19.23 | 500  | 1.1289          | 0.4155 |
| 0.2088        | 23.08 | 600  | 0.9339          | 0.3623 |
| 0.1388        | 26.91 | 700  | 1.1448          | 0.3573 |
| 0.1042        | 30.75 | 800  | 1.1411          | 0.3606 |
| 0.0784        | 34.6  | 900  | 1.2046          | 0.3547 |
| 0.0607        | 38.45 | 1000 | 1.2243          | 0.3488 |
| 0.0459        | 42.3  | 1100 | 1.2387          | 0.3226 |
| 0.0273        | 46.15 | 1200 | 1.2123          | 0.3387 |
| 0.0195        | 49.98 | 1300 | 1.2232          | 0.3345 |
| 0.0188        | 53.83 | 1400 | 1.2656          | 0.3235 |
| 0.0132        | 57.68 | 1500 | 1.3377          | 0.3285 |
| 0.0089        | 61.53 | 1600 | 1.3193          | 0.3235 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
