---
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-common_voice-tr-ft
  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. -->

# wav2vec2-large-xls-r-300m-common_voice-tr-ft

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3527
- Wer: 0.3212
- Cer: 0.0750

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.7897        | 9.09  | 500  | 0.4873          | 0.6006 | 0.1491 |
| 0.5166        | 18.18 | 1000 | 0.4058          | 0.4238 | 0.1070 |
| 0.4012        | 27.27 | 1500 | 0.3716          | 0.3781 | 0.0935 |
| 0.3851        | 36.36 | 2000 | 0.3565          | 0.3458 | 0.0836 |
| 0.2212        | 45.45 | 2500 | 0.3580          | 0.3272 | 0.0766 |


### Framework versions

- Transformers 4.13.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.15.2.dev0
- Tokenizers 0.10.3