ylacombe / wav2vec2-common_voice-af-demo

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30-day runs: 155
Model's Last Updated: January 02 2024
automatic-speech-recognition

Introduction of wav2vec2-common_voice-af-demo

Model Details of wav2vec2-common_voice-af-demo

wav2vec2-common_voice-af-demo

This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the MOZILLA-FOUNDATION/COMMON_VOICE_16_0 - AF dataset. It achieves the following results on the evaluation set:

  • Loss: inf
  • Wer: 1.0
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: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 15.0
  • mixed_precision_training: Native AMP
Training results
Framework versions
  • Transformers 4.37.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.15.0

Runs of ylacombe wav2vec2-common_voice-af-demo on huggingface.co

164
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3-day runs
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7-day runs
155
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More Information About wav2vec2-common_voice-af-demo huggingface.co Model

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wav2vec2-common_voice-af-demo install

wav2vec2-common_voice-af-demo is an open source model from GitHub that offers a free installation service, and any user can find wav2vec2-common_voice-af-demo on GitHub to install. At the same time, huggingface.co provides the effect of wav2vec2-common_voice-af-demo install, users can directly use wav2vec2-common_voice-af-demo installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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