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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: wav2vec2-augmented-vivos
    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: 0.2447200155008719

wav2vec2-augmented-vivos

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: 0.4403
  • Wer: 0.2447

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: 0.0002
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.3
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.6691 2.0 146 4.0324 1.0
3.4795 4.0 292 3.6294 1.0
3.4178 6.0 438 3.4910 1.0
1.8415 8.0 584 0.7926 0.5287
0.5336 10.0 730 0.5809 0.3677
0.3349 12.0 876 0.4679 0.2853
0.2424 14.0 1022 0.4440 0.2680
0.2193 16.0 1168 0.4420 0.2536
0.1627 18.0 1314 0.4373 0.2455
0.1532 20.0 1460 0.4403 0.2447

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1