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rohitp1/libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-5

sourceHugging Faceupdated 4y agoView on Hugging Face
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libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-5

This model is a fine-tuned version of rohitp1/libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-3 on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 30.3050
  • —Wer: 0.2650

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: 4
  • —evalbatchsize: 1
  • —seed: 42
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 64
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.2
  • —num_epochs: 100
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
239.48651.1240031.08360.2908
210.20462.2580029.78310.2742
195.04783.37120028.87940.2636
188.80964.49160028.74580.2600
183.65925.62200029.11590.2573
181.50256.74240029.00810.2564
181.99547.86280028.71320.2588
181.85488.99320029.32070.2630
186.252410.11360029.91190.2593
188.383811.24400030.29630.2627
192.262312.36440030.30500.2650

Framework versions

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