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

sourceHugging Faceupdated 4y agoView on Hugging Face
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Model Card

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libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse-take-3

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

  • —Loss: 28.9263
  • —Wer: 0.3301

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: 0.0005
  • —trainbatchsize: 4
  • —evalbatchsize: 1
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 8
  • —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
291.10880.2240028.42070.3362
284.19680.4580028.14580.3314
288.14140.67120028.13970.3326
290.02720.9160028.41860.3323
287.32241.12200028.35480.3283
279.14821.35240028.53730.3309
285.82171.57280028.44470.3301
282.92651.79320028.53790.3365
292.62542.02360028.26320.3299
279.2152.24400028.92630.3301

Framework versions

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