whisper-tiny-speech-commands
This model is a fine-tuned version of openai/whisper-tiny on the speech_commands dataset. It achieves the following results on the evaluation set:
- Loss: 1.3232
- Accuracy: 0.8040
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: 96
- eval_batch_size: 96
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4229 | 1.0 | 412 | 1.1286 | 0.7936 |
| 0.1396 | 2.0 | 824 | 1.0506 | 0.7995 |
| 0.1323 | 3.0 | 1236 | 1.1224 | 0.7977 |
| 0.0528 | 4.0 | 1648 | 1.0810 | 0.8004 |
| 0.0889 | 5.0 | 2060 | 0.9224 | 0.8022 |
| 0.076 | 6.0 | 2472 | 1.0393 | 0.7981 |
| 0.0429 | 7.0 | 2884 | 1.1115 | 0.7990 |
| 0.0007 | 8.0 | 3296 | 1.1706 | 0.8026 |
| 0.0129 | 9.0 | 3708 | 1.0661 | 0.8013 |
| 0.0161 | 10.0 | 4120 | 1.0114 | 0.7990 |
| 0.0205 | 11.0 | 4532 | 1.2129 | 0.8031 |
| 0.0107 | 12.0 | 4944 | 1.1118 | 0.8026 |
| 0.0099 | 13.0 | 5356 | 0.9145 | 0.8031 |
| 0.0002 | 14.0 | 5768 | 1.1582 | 0.7999 |
| 0.0001 | 15.0 | 6180 | 1.2959 | 0.8035 |
| 0.0163 | 16.0 | 6592 | 1.0992 | 0.8026 |
| 0.0001 | 17.0 | 7004 | 1.2913 | 0.8035 |
| 0.0003 | 18.0 | 7416 | 1.3232 | 0.8040 |
| 0.0001 | 19.0 | 7828 | 1.3720 | 0.8040 |
| 0.0001 | 20.0 | 8240 | 1.3889 | 0.8040 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1