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metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod16
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: id
          split: test
          args: id
        metrics:
          - type: wer
            value: 0.31356010324483774
            name: Wer

wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod16

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3425
  • Wer: 0.3136

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: 16
  • 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
2.9562 1.0 278 2.9246 1.0
2.8689 2.0 556 2.7856 1.0
1.1264 3.0 834 0.6656 0.6370
0.6913 4.0 1112 0.5009 0.5000
0.5835 5.0 1390 0.4370 0.4477
0.4684 6.0 1668 0.3923 0.3857
0.4139 7.0 1946 0.3876 0.3761
0.389 8.0 2224 0.3881 0.3551
0.3559 9.0 2502 0.3580 0.3387
0.3228 10.0 2780 0.3552 0.3249
0.3295 11.0 3058 0.3385 0.3197
0.3112 12.0 3336 0.3425 0.3136

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1