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metadata
license: cc-by-sa-4.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: wav2vec2-detect-toxic-th
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice
          type: common_voice
          config: th
          split: validation
          args: th
        metrics:
          - name: Wer
            type: wer
            value: 0.4536376604850214

wav2vec2-detect-toxic-th

This model is a fine-tuned version of airesearch/wav2vec2-large-xlsr-53-th on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2174
  • Wer: 0.4536

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
5.3619 3.23 100 3.2891 1.0
3.299 6.45 200 3.1670 1.0
2.1179 9.68 300 1.1747 0.5221
1.1047 12.9 400 1.0323 0.5849
0.8974 16.13 500 1.0128 0.5029
0.769 19.35 600 1.0402 0.4957
0.6659 22.58 700 1.0902 0.4729
0.6114 25.81 800 1.1412 0.4629
0.5511 29.03 900 1.1156 0.4643
0.5137 32.26 1000 1.1556 0.4679
0.5132 35.48 1100 1.1851 0.4515
0.4583 38.71 1200 1.1971 0.4529
0.4523 41.94 1300 1.2182 0.4579
0.4329 45.16 1400 1.2178 0.4586
0.4502 48.39 1500 1.2174 0.4536

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 1.16.1
  • Tokenizers 0.13.3