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rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-4

sourceHugging Faceupdated 4y agoView on Hugging Face
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libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-4

This model is a fine-tuned version of rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-2 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 37.5364
  • —Wer: 0.3334

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: 0.002
  • —trainbatchsize: 2
  • —evalbatchsize: 1
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.2
  • —num_epochs: 40
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
43.78060.940041.30730.2570
48.65491.880041.89450.2740
57.42092.7120039.99470.2872
68.84493.59160039.45280.3059
79.42994.49200038.95750.3179
93.05145.39240037.53640.3334

Framework versions

  • —Transformers 4.24.0
  • —Pytorch 1.12.1
  • —Datasets 2.7.1
  • —Tokenizers 0.11.0