---
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: ''
  results: []
---

<!-- 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. -->

# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7314
- Wer: 0.4692
- Cer: 0.1321

## 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: 0.0005
- 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: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.0779        | 4.59  | 500   | 0.8260          | 0.7395 | 0.2354 |
| 0.7573        | 9.17  | 1000  | 0.7544          | 0.6960 | 0.2100 |
| 0.8225        | 13.76 | 1500  | 0.6867          | 0.6672 | 0.2021 |
| 0.621         | 18.35 | 2000  | 0.6824          | 0.6209 | 0.1874 |
| 0.6362        | 22.94 | 2500  | 0.6712          | 0.6286 | 0.1904 |
| 0.624         | 27.52 | 3000  | 0.6940          | 0.6116 | 0.1820 |
| 0.4781        | 32.11 | 3500  | 0.6966          | 0.5989 | 0.1735 |
| 0.5685        | 36.7  | 4000  | 0.6742          | 0.5971 | 0.1769 |
| 0.4384        | 41.28 | 4500  | 0.6904          | 0.5999 | 0.1767 |
| 0.5509        | 45.87 | 5000  | 0.6734          | 0.5641 | 0.1692 |
| 0.3665        | 50.46 | 5500  | 0.7018          | 0.5662 | 0.1680 |
| 0.3914        | 55.05 | 6000  | 0.7121          | 0.5552 | 0.1631 |
| 0.2467        | 59.63 | 6500  | 0.6657          | 0.5374 | 0.1563 |
| 0.2576        | 64.22 | 7000  | 0.6920          | 0.5316 | 0.1554 |
| 0.2711        | 68.81 | 7500  | 0.6900          | 0.5176 | 0.1495 |
| 0.2626        | 73.39 | 8000  | 0.6843          | 0.5043 | 0.1454 |
| 0.1377        | 77.98 | 8500  | 0.7383          | 0.5101 | 0.1470 |
| 0.2005        | 82.57 | 9000  | 0.7228          | 0.5045 | 0.1430 |
| 0.1355        | 87.16 | 9500  | 0.7231          | 0.4869 | 0.1375 |
| 0.0431        | 91.74 | 10000 | 0.7397          | 0.4749 | 0.1350 |
| 0.0586        | 96.33 | 10500 | 0.7360          | 0.4754 | 0.1339 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0