wav2vec2-base-finetuned-ks
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0015
- Accuracy: 0.9997
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0069 | 1.0 | 421 | 0.0040 | 0.9994 |
0.0075 | 2.0 | 842 | 0.0122 | 0.9966 |
0.0003 | 3.0 | 1263 | 0.0049 | 0.9994 |
0.0003 | 4.0 | 1684 | 0.0032 | 0.9994 |
0.0001 | 5.0 | 2105 | 0.0015 | 0.9997 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 2.11.0
- Tokenizers 0.21.0
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Model tree for oyamat/wav2vec2-base-finetuned-ks
Base model
facebook/wav2vec2-baseEvaluation results
- Accuracy on audiofoldervalidation set self-reported1.000