distilhubert-finetuned-breathiness-finetuned-breathiness_fewshot
This model is a fine-tuned version of NiloofarMomeni/distilhubert-finetuned-breathiness on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7120
- Accuracy: 0.8283
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch 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 |
---|---|---|---|---|
0.2935 | 1.0 | 47 | 0.5536 | 0.7980 |
0.4634 | 2.0 | 94 | 0.4524 | 0.7980 |
0.4697 | 3.0 | 141 | 0.4134 | 0.8081 |
0.371 | 4.0 | 188 | 0.4501 | 0.8182 |
0.4197 | 5.0 | 235 | 0.5902 | 0.8081 |
0.1565 | 6.0 | 282 | 0.6938 | 0.8081 |
0.1828 | 7.0 | 329 | 0.6856 | 0.8283 |
0.5466 | 8.0 | 376 | 0.8179 | 0.8182 |
0.3124 | 9.0 | 423 | 0.6968 | 0.8283 |
0.2355 | 10.0 | 470 | 0.7120 | 0.8283 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0
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Model tree for NiloofarMomeni/distilhubert-finetuned-breathiness-finetuned-breathiness_fewshot
Base model
ntu-spml/distilhubert