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wav2vec2-base

This model is a fine-tuned version of facebook/wav2vec2-base on the galsenai/waxal_dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7504
  • Accuracy: 0.8632
  • Precision: 0.9380
  • F1: 0.8954

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: 30
  • eval_batch_size: 30
  • seed: 0
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 120
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 32.0

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision F1
4.3647 2.53 500 4.8202 0.0117 0.0134 0.0032
2.6202 5.05 1000 4.2238 0.0625 0.0781 0.0355
1.38 7.58 1500 3.6392 0.2941 0.5211 0.3174
0.8601 10.1 2000 2.7953 0.4907 0.7446 0.5657
0.5645 12.63 2500 1.9829 0.6862 0.8363 0.7421
0.4009 15.15 3000 1.4535 0.7635 0.9000 0.8174
0.3054 17.68 3500 1.1426 0.7882 0.9058 0.8298
0.2448 20.2 4000 0.9860 0.8189 0.9206 0.8593
0.2116 22.73 4500 0.8820 0.8325 0.9261 0.8711
0.1863 25.25 5000 0.8191 0.8465 0.9366 0.8848
0.1701 27.78 5500 0.7504 0.8632 0.9380 0.8954
0.1558 30.3 6000 0.7665 0.8609 0.9398 0.8956

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 2.9.1.dev0
  • Tokenizers 0.13.2
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