asakawa / wav2vec2-base-demo-colab

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: 1
30-day runs: -2
Model's Last Updated: January 12 2022
automatic-speech-recognition

Introduction of wav2vec2-base-demo-colab

Model Details of wav2vec2-base-demo-colab

wav2vec2-base-demo-colab

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4500
  • Wer: 0.3391
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: 8
  • 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: 30
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
3.5329 4.0 500 1.5741 1.0400
0.6432 8.0 1000 0.4571 0.4418
0.2214 12.0 1500 0.4381 0.3823
0.1294 16.0 2000 0.4706 0.3911
0.0868 20.0 2500 0.5252 0.3662
0.0616 24.0 3000 0.4828 0.3458
0.0461 28.0 3500 0.4500 0.3391
Framework versions
  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.14.0
  • Tokenizers 0.10.3

Runs of asakawa wav2vec2-base-demo-colab on huggingface.co

5
Total runs
0
24-hour runs
1
3-day runs
1
7-day runs
-2
30-day runs

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