---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- accuracy
model-index:
- name: wav2vec2_turkish_gender_classification
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: tr
      split: test
      args: tr
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8478508073686605
---

<!-- 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_turkish_gender_classification

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7567
- Accuracy: 0.8479

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1723        | 0.9968 | 233  | 0.5006          | 0.8003   |
| 0.0967        | 1.9979 | 467  | 0.3800          | 0.8722   |
| 0.0696        | 2.9989 | 701  | 0.5256          | 0.8449   |
| 0.0451        | 4.0    | 935  | 0.5080          | 0.8879   |
| 0.0647        | 4.9968 | 1168 | 0.5977          | 0.8551   |
| 0.0322        | 5.9979 | 1402 | 0.7294          | 0.8463   |
| 0.0249        | 6.9989 | 1636 | 1.0826          | 0.7830   |
| 0.0189        | 8.0    | 1870 | 0.6995          | 0.8485   |
| 0.0276        | 8.9968 | 2103 | 0.8064          | 0.8360   |
| 0.0167        | 9.9679 | 2330 | 0.7567          | 0.8479   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1