wav2vec2_turkish_gender_classification
This model is a fine-tuned version of 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
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Base model
facebook/wav2vec2-baseSpace using candenizkocak/wav2vec2_turkish_gender_classification 1
Evaluation results
- Accuracy on common_voice_17_0test set self-reported0.848