---
language:
- tr
license: cc-by-nc-4.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
- mms
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-tr-mms-demo-3
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: COMMON_VOICE - TR
      type: common_voice
      config: tr
      split: test
      args: 'Config: tr, Training split: train+validation, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.2267388417934838
---

<!-- 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-common_voice-tr-mms-demo

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1532
- Wer: 0.2267

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.92  | 100  | 0.1822          | 0.2605 |
| No log        | 1.83  | 200  | 0.1620          | 0.2389 |
| No log        | 2.75  | 300  | 0.1581          | 0.2318 |
| No log        | 3.67  | 400  | 0.1535          | 0.2270 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3