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Benchmark
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superb_ks_42
This model is a fine-tuned version of facebook/wav2vec2-large on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.0856
- Accuracy: 0.9840
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: 32
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0646 | 1.0 | 1597 | 0.1839 | 0.9625 |
| 0.3751 | 2.0 | 3194 | 0.1954 | 0.9647 |
| 0.3156 | 3.0 | 4791 | 0.1335 | 0.9744 |
| 0.257 | 4.0 | 6388 | 0.1062 | 0.9796 |
| 0.2386 | 5.0 | 7985 | 0.1029 | 0.9801 |
| 0.2085 | 6.0 | 9582 | 0.1002 | 0.9815 |
| 0.1715 | 7.0 | 11179 | 0.1031 | 0.9818 |
| 0.1575 | 8.0 | 12776 | 0.0938 | 0.9819 |
| 0.1332 | 9.0 | 14373 | 0.0896 | 0.9831 |
| 0.1288 | 10.0 | 15970 | 0.0856 | 0.9840 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for jialicheng/wav2vec2-large-speech_commands
Base model
facebook/wav2vec2-large