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speech-seq2seq/wav2vec2-2-bert-large-no-adapter

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: 6.9251
  • —Wer: 1.7858

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: 3e-05
  • —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
6.64870.285006.83541.4719
6.56620.5610006.78770.9371
6.43090.8415006.76401.1317
6.71231.1220006.79071.9354
6.75471.425006.78301.8854
6.67261.6830006.82111.9203
6.65381.9635006.84441.8235
6.56932.2440006.88731.8606
6.72342.5245006.86491.8126
6.51042.850006.92511.7858

Framework versions

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