wav2vec2-base-ft-keyword-spotting
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.0782
- Accuracy: 0.9832
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: 0
- 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: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5065 | 0.9994 | 399 | 0.3426 | 0.9713 |
| 0.2089 | 1.9987 | 798 | 0.1267 | 0.9781 |
| 0.1834 | 2.9981 | 1197 | 0.0889 | 0.9804 |
| 0.142 | 4.0 | 1597 | 0.0854 | 0.9813 |
| 0.1472 | 4.9969 | 1995 | 0.0782 | 0.9832 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for HenryXu1/wav2vec2-base-ft-keyword-spotting
Base model
facebook/wav2vec2-base