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wav2vec2-base-gumbelVQ-timit-fine-tuned

This model is a fine-tuned version of wav2vec2-pretrained-base-gumbelVQ on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7549
  • Wer: 0.4902

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: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20.0

Training results

Training Loss Epoch Step Validation Loss Wer
0.4628 10.0 1450 0.6779 0.5171
0.3036 20.0 2900 0.7549 0.4902

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.3.0.dev20231229+cu118
  • Datasets 2.16.0
  • Tokenizers 0.15.0
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Dataset used to train subatomicseer/wav2vec2-base-gumbelVQ-timit-fine-tuned

Evaluation results