wav2vec2-base-finetuned-ks
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: 1.5562
- Accuracy: 0.9632
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: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.5366 | 1.0 | 83 | 2.2424 | 0.8575 |
1.963 | 2.0 | 166 | 1.6987 | 0.9537 |
1.7887 | 3.0 | 249 | 1.5562 | 0.9632 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for realHarter/wav2vec2-base-finetuned-ks
Base model
facebook/wav2vec2-baseDataset used to train realHarter/wav2vec2-base-finetuned-ks
Evaluation results
- Accuracy on speech_commandsvalidation set self-reported0.963