---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: model_finetuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ru
      split: test
      args: ru
    metrics:
    - name: Wer
      type: wer
      value: 0.5240747438215793
---

<!-- 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. -->

# model_finetuned

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_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4337
- Wer: 0.5241

## 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: 24
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.1665        | 1.9139  | 400  | 1.3007          | 0.9612 |
| 0.9389        | 3.8278  | 800  | 0.6428          | 0.7616 |
| 0.5785        | 5.7416  | 1200 | 0.5126          | 0.6447 |
| 0.4408        | 7.6555  | 1600 | 0.4807          | 0.5937 |
| 0.3589        | 9.5694  | 2000 | 0.4581          | 0.5665 |
| 0.3033        | 11.4833 | 2400 | 0.4461          | 0.5416 |
| 0.2678        | 13.3971 | 2800 | 0.4337          | 0.5241 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1