w2v2-ks-jpqd-quant-FE-finetuned-student
This model is a fine-tuned version of anton-l/wav2vec2-base-ft-keyword-spotting on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.0869
- Accuracy: 0.9794
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: 7e-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: 0.5
- num_epochs: 12.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3477 | 1.0 | 399 | 0.1516 | 0.9637 |
| 5.5957 | 2.0 | 798 | 5.4798 | 0.9545 |
| 8.7806 | 3.0 | 1197 | 8.6491 | 0.9634 |
| 10.4524 | 4.0 | 1596 | 10.2701 | 0.9554 |
| 10.8964 | 5.0 | 1995 | 10.7809 | 0.9647 |
| 10.9322 | 6.0 | 2394 | 10.7806 | 0.9619 |
| 0.2389 | 7.0 | 2793 | 0.1148 | 0.9738 |
| 0.2522 | 8.0 | 3192 | 0.1013 | 0.9747 |
| 0.2213 | 9.0 | 3591 | 0.0983 | 0.9754 |
| 0.2053 | 10.0 | 3990 | 0.0934 | 0.9768 |
| 0.1543 | 11.0 | 4389 | 0.0875 | 0.9779 |
| 0.1836 | 12.0 | 4788 | 0.0869 | 0.9794 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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