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wav2vec2-base-speech-recoginition

Automatic Speech Recognition
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wav2vec2
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Eval Results (legacy)
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wav2vec2-base-speech-recoginition

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

  • Loss: 4.0532
  • Wer: 0.9985

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: 0.002
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.9304 1.85 500 4.0532 0.9985

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.0.0
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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Base model

facebook/wav2vec2-base
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Dataset used to train Puyush/wav2vec2-base-speech-recoginition

Space using Puyush/wav2vec2-base-speech-recoginition 1

Evaluation results