wav2vec2-base-finetuned-speech_commands-v0.01
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: 1.3035
 - Accuracy: 0.9410
 
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 | 
|---|---|---|---|---|
| 2.8093 | 1.0 | 80 | 2.6146 | 0.8676 | 
| 2.0284 | 2.0 | 160 | 1.8246 | 0.9282 | 
| 1.7136 | 3.0 | 240 | 1.5052 | 0.9394 | 
| 1.5324 | 4.0 | 320 | 1.3487 | 0.9391 | 
| 1.4979 | 5.0 | 400 | 1.3035 | 0.9410 | 
Framework versions
- Transformers 4.27.4
 - Pytorch 2.0.0+cu118
 - Datasets 2.11.0
 - Tokenizers 0.13.3
 
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