wav2vec2-base-finetuned-ks
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 0.0977
- Accuracy: 0.9822
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 |
|---|---|---|---|---|
| 0.6403 | 1.0 | 400 | 0.6115 | 0.8597 |
| 0.2764 | 2.0 | 800 | 0.1926 | 0.9773 |
| 0.2263 | 3.0 | 1200 | 0.1171 | 0.9810 |
| 0.1638 | 4.0 | 1600 | 0.0977 | 0.9822 |
| 0.1313 | 5.0 | 2000 | 0.0909 | 0.9822 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for Hnin/wav2vec2-base-finetuned-ks
Base model
facebook/wav2vec2-baseDataset used to train Hnin/wav2vec2-base-finetuned-ks
Space using Hnin/wav2vec2-base-finetuned-ks 1
Evaluation results
- Accuracy on superbvalidation set self-reported0.982