---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-tr-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice
      type: common_voice
      config: tr
      split: test
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 0.3005821672964968
---

<!-- 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-tr-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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3889
- Wer: 0.3006

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.8274        | 3.67  | 400  | 0.6752          | 0.6946 |
| 0.4002        | 7.34  | 800  | 0.4440          | 0.5183 |
| 0.1961        | 11.01 | 1200 | 0.4133          | 0.4052 |
| 0.1285        | 14.68 | 1600 | 0.4249          | 0.3737 |
| 0.0966        | 18.35 | 2000 | 0.4019          | 0.3606 |
| 0.0789        | 22.02 | 2400 | 0.4019          | 0.3316 |
| 0.0599        | 25.69 | 2800 | 0.3996          | 0.3078 |
| 0.047         | 29.36 | 3200 | 0.3889          | 0.3006 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3