pytorch wav2vec2 automatic-speech-recognition tr dataset:common_voice transformers common_voice generated_from_trainer license:apache-2.0 model-index
---
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-common_voice-tr-demo-dist
  results: []
---

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# wav2vec2-common_voice-tr-demo-dist

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3848
- Wer: 0.3242

## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_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: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.5279        | 0.46  | 100  | 3.6260          | 1.0    |
| 3.1065        | 0.92  | 200  | 3.0854          | 0.9999 |
| 1.4111        | 1.38  | 300  | 1.3343          | 0.8839 |
| 0.8468        | 1.83  | 400  | 0.6920          | 0.6826 |
| 0.6242        | 2.29  | 500  | 0.6001          | 0.5996 |
| 0.4181        | 2.75  | 600  | 0.5655          | 0.5680 |
| 0.4311        | 3.21  | 700  | 0.4478          | 0.5003 |
| 0.3601        | 3.67  | 800  | 0.4548          | 0.5011 |
| 0.2756        | 4.13  | 900  | 0.4444          | 0.4682 |
| 0.2373        | 4.59  | 1000 | 0.4111          | 0.4432 |
| 0.1831        | 5.05  | 1100 | 0.4178          | 0.4447 |
| 0.2423        | 5.5   | 1200 | 0.3881          | 0.4277 |
| 0.2128        | 5.96  | 1300 | 0.3865          | 0.4018 |
| 0.1256        | 6.42  | 1400 | 0.3818          | 0.4137 |
| 0.1038        | 6.88  | 1500 | 0.3739          | 0.3942 |
| 0.1662        | 7.34  | 1600 | 0.3938          | 0.3929 |
| 0.198         | 7.8   | 1700 | 0.3831          | 0.3837 |
| 0.0728        | 8.26  | 1800 | 0.3910          | 0.3867 |
| 0.123         | 8.72  | 1900 | 0.3722          | 0.3735 |
| 0.0776        | 9.17  | 2000 | 0.3938          | 0.3725 |
| 0.1597        | 9.63  | 2100 | 0.3786          | 0.3697 |
| 0.1124        | 10.09 | 2200 | 0.3947          | 0.3590 |
| 0.0965        | 10.55 | 2300 | 0.3952          | 0.3562 |
| 0.0612        | 11.01 | 2400 | 0.3810          | 0.3476 |
| 0.0764        | 11.47 | 2500 | 0.3734          | 0.3507 |
| 0.0973        | 11.93 | 2600 | 0.3935          | 0.3472 |
| 0.0649        | 12.39 | 2700 | 0.3672          | 0.3413 |
| 0.0542        | 12.84 | 2800 | 0.3732          | 0.3369 |
| 0.087         | 13.3  | 2900 | 0.3833          | 0.3458 |
| 0.0196        | 13.76 | 3000 | 0.3761          | 0.3303 |
| 0.0548        | 14.22 | 3100 | 0.3855          | 0.3274 |
| 0.0577        | 14.68 | 3200 | 0.3893          | 0.3238 |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.2.1
- Tokenizers 0.12.1
