CoolFace
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speech-seq2seq/wav2vec2-2-bert-large

sourceHugging Faceupdated 5y agoView on Hugging Face
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Model Card

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This model was trained from scratch on the librispeech_asr dataset. It achieves the following results on the evaluation set:

  • Loss: 6.9670
  • Wer: 1.9878

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
  • trainbatchsize: 8
  • evalbatchsize: 8
  • seed: 42
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 3.0
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
6.75990.285006.87551.2551
6.59430.5610006.77021.5878
6.31460.8415006.69811.6627
6.61121.1220006.67601.9853
6.68941.425006.63231.9376
6.55251.6830006.61851.9383
6.5711.9635006.61261.9580
6.33632.2440006.78691.9818
6.58322.5245006.90962.0025
6.35232.850006.96701.9878

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0