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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod14
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: id
          split: test
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 0.9999539085545722

wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod14

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9481
  • Wer: 1.0000

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: 0.003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.9078 1.0 556 2.9342 1.0
2.875 2.0 1112 2.8557 1.0
2.6528 3.0 1668 2.5665 1.0000
2.386 4.0 2224 2.3012 1.0000
2.3101 5.0 2780 2.1943 0.9999
2.2018 6.0 3336 2.1332 1.0
2.1752 7.0 3892 2.0791 1.0
2.1255 8.0 4448 2.0347 1.0
2.0975 9.0 5004 2.0129 1.0
2.0718 10.0 5560 1.9677 1.0
2.0771 11.0 6116 1.9591 1.0
2.0516 12.0 6672 1.9481 1.0000

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2