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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - vivos
metrics:
  - wer
model-index:
  - name: working
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: vivos
          type: vivos
          config: default
          split: None
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.1690242779130206

working

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

  • Loss: 0.2700
  • Wer: 0.1690

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: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.2111 2.0 292 0.9069 0.5315
0.6195 4.0 584 0.4762 0.3436
0.4338 6.0 876 0.3627 0.2657
0.3471 8.0 1168 0.4132 0.2817
0.2897 10.0 1460 0.3098 0.2178
0.2471 12.0 1752 0.2761 0.1957
0.2184 14.0 2044 0.2694 0.1807
0.1927 16.0 2336 0.2705 0.1753
0.1754 18.0 2628 0.2692 0.1709
0.1622 20.0 2920 0.2700 0.1690

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1