wav2vec2-base-finetuned-speech_commands-v0.02
This model is a fine-tuned version of facebook/wav2vec2-base on the speech_commands dataset. It achieves the following results on the evaluation set:
- Loss: 0.1170
- Accuracy: 0.9759
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: 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: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9963 | 1.0 | 663 | 0.7316 | 0.9612 |
| 0.4965 | 2.0 | 1326 | 0.2656 | 0.9672 |
| 0.4306 | 3.0 | 1989 | 0.1630 | 0.9720 |
| 0.2901 | 4.0 | 2652 | 0.1283 | 0.9753 |
| 0.2963 | 5.0 | 3315 | 0.1170 | 0.9759 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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