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neunit-ks-20230509V3
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: 0.1696
- Accuracy: 0.9816
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: 0
- 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: 5.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5857 | 0.99 | 53 | 0.4074 | 0.9329 |
0.2251 | 2.0 | 107 | 0.1696 | 0.9816 |
0.1465 | 2.99 | 160 | 0.1284 | 0.975 |
0.1169 | 4.0 | 214 | 0.0939 | 0.9803 |
0.1153 | 4.95 | 265 | 0.0930 | 0.9789 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3