transformers pytorch tensorboard wav2vec2 automatic-speech-recognition mozilla-foundation/common_voice_13_0 generated_from_trainer de dataset:common_voice_13_0 base_model:facebook/wav2vec2-large-xlsr-53 license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- de
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_13_0
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-german-cv13-restart
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - DE
      type: common_voice_13_0
      config: de
      split: test
      args: 'Config: de, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.10748248671697858
---

<!-- 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. -->

# wav2vec2-large-xlsr-53-german-cv13-restart

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_13_0 - DE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1121
- Wer: 0.1075
- Cer: 0.0286

## 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: 32
- eval_batch_size: 16
- 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: 0.01
- num_epochs: 15.0

### Training results

| Training Loss | Epoch | Step  | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 0.1679        | 1.0   | 4348  | 0.0459 | 0.1617          | 0.1707 |
| 0.1597        | 2.0   | 8697  | 0.0479 | 0.1592          | 0.1717 |
| 0.1364        | 3.0   | 13045 | 0.0425 | 0.1524          | 0.1563 |
| 0.1311        | 4.0   | 17394 | 0.0406 | 0.1446          | 0.1515 |
| 0.1152        | 5.0   | 21742 | 0.0397 | 0.1431          | 0.1470 |
| 0.107         | 6.0   | 26091 | 0.0369 | 0.1382          | 0.1377 |
| 0.0957        | 7.0   | 30439 | 0.0373 | 0.1343          | 0.1372 |
| 0.0924        | 8.0   | 34788 | 0.0355 | 0.1335          | 0.1315 |
| 0.0835        | 9.0   | 39136 | 0.0384 | 0.1328          | 0.1380 |
| 0.0775        | 10.0  | 43485 | 0.0328 | 0.1232          | 0.1229 |
| 0.0752        | 11.0  | 47833 | 0.0309 | 0.1220          | 0.1174 |
| 0.0691        | 12.0  | 52182 | 0.0327 | 0.1182          | 0.1197 |
| 0.0689        | 13.0  | 56530 | 0.0307 | 0.1163          | 0.1150 |
| 0.0653        | 14.0  | 60879 | 0.0304 | 0.1141          | 0.1126 |
| 0.0717        | 15.0  | 65220 | 0.1121 | 0.1075          | 0.0286 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.0
