audio_kor
This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3679
- Accuracy: 0.9496
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.6342 | 1.0 | 30 | 2.6301 | 0.0588 |
2.4757 | 2.0 | 60 | 2.3899 | 0.3109 |
1.9266 | 3.0 | 90 | 1.8527 | 0.6134 |
1.5614 | 4.0 | 120 | 1.4405 | 0.7227 |
0.9955 | 5.0 | 150 | 1.0447 | 0.8655 |
0.6666 | 6.0 | 180 | 0.7428 | 0.9076 |
0.4623 | 7.0 | 210 | 0.5859 | 0.9160 |
0.334 | 8.0 | 240 | 0.4750 | 0.9244 |
0.2673 | 9.0 | 270 | 0.3788 | 0.9496 |
0.196 | 10.0 | 300 | 0.3679 | 0.9496 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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Model tree for heado/audio_kor
Base model
Kkonjeong/wav2vec2-base-korean