wav2vec2_classifier_arabic
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6082
- Accuracy: 0.8571
- Precision: 0.8713
- Recall: 0.8571
- F1: 0.8549
- Binary: 0.9002
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: 6.255516869030134e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 2000
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
---|---|---|---|---|---|---|---|---|
4.4473 | 1.0 | 109 | 4.4217 | 0.0257 | 0.0267 | 0.0257 | 0.0125 | 0.1703 |
4.2304 | 2.0 | 219 | 4.0329 | 0.1027 | 0.0299 | 0.1027 | 0.0402 | 0.3658 |
3.9161 | 3.0 | 328 | 3.6520 | 0.1637 | 0.1035 | 0.1637 | 0.0937 | 0.4124 |
3.5075 | 4.0 | 438 | 3.2131 | 0.3098 | 0.2155 | 0.3098 | 0.2227 | 0.5165 |
3.1463 | 5.0 | 547 | 2.7609 | 0.4494 | 0.3587 | 0.4494 | 0.3650 | 0.6128 |
2.7101 | 6.0 | 657 | 2.2656 | 0.6148 | 0.5661 | 0.6148 | 0.5558 | 0.7300 |
2.3391 | 7.0 | 766 | 1.8535 | 0.6918 | 0.6991 | 0.6918 | 0.6567 | 0.7841 |
1.977 | 8.0 | 876 | 1.4528 | 0.7640 | 0.7554 | 0.7640 | 0.7389 | 0.8350 |
1.7077 | 9.0 | 985 | 1.2586 | 0.7673 | 0.7744 | 0.7673 | 0.7504 | 0.8353 |
1.4602 | 10.0 | 1095 | 1.0169 | 0.8154 | 0.8373 | 0.8154 | 0.8054 | 0.8711 |
1.2622 | 11.0 | 1204 | 0.8802 | 0.8250 | 0.8503 | 0.8250 | 0.8227 | 0.8772 |
1.1108 | 12.0 | 1314 | 0.7670 | 0.8315 | 0.8572 | 0.8315 | 0.8259 | 0.8812 |
0.9983 | 13.0 | 1423 | 0.7210 | 0.8427 | 0.8666 | 0.8427 | 0.8412 | 0.8905 |
0.8929 | 14.0 | 1533 | 0.6566 | 0.8411 | 0.8594 | 0.8411 | 0.8375 | 0.8894 |
0.8259 | 15.0 | 1642 | 0.6354 | 0.8539 | 0.8684 | 0.8539 | 0.8509 | 0.8979 |
0.7617 | 16.0 | 1752 | 0.6634 | 0.8507 | 0.8669 | 0.8507 | 0.8483 | 0.8957 |
0.7255 | 17.0 | 1861 | 0.6046 | 0.8571 | 0.8689 | 0.8571 | 0.8547 | 0.9006 |
0.6853 | 18.0 | 1971 | 0.6096 | 0.8587 | 0.8757 | 0.8587 | 0.8555 | 0.9013 |
0.666 | 18.26 | 2000 | 0.6082 | 0.8571 | 0.8713 | 0.8571 | 0.8549 | 0.9002 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.13.3
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