---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-turkish-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: tr
      split: test
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 0.7091714338438826
---

<!-- 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-turkish-colab

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_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5247
- Wer: 0.7092

## 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: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1953        | 3.86  | 400  | 0.5740          | 0.7963 |
| 0.1959        | 7.73  | 800  | 0.5169          | 0.7743 |
| 0.1486        | 11.59 | 1200 | 0.5334          | 0.7501 |
| 0.1146        | 15.46 | 1600 | 0.5186          | 0.7226 |
| 0.0885        | 19.32 | 2000 | 0.5247          | 0.7092 |


### Framework versions

- Transformers 4.36.1
- Pytorch 1.10.0+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0