CoolFace
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artyomboyko/whisper-small-ru-v2

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Whisper-small-ru-v2

This model is a fine-tuned version of openai/whisper-small on an Russian part of the Common Voice 15 dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.1329
  • —Wer: 12.6750
  • —Cer: 3.7305
  • —Learning Rate: 0.0000

Model description

Same as openai/whisper-small.

Intended uses & limitations

Same as openai/whisper-small

Training and evaluation data

Fine-tunned on an Russian part of the Common Voice 15 dataset.

Training procedure

According to the article "Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers"

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 5e-08
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 250
  • —training_steps: 15000
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWerCerRate
0.06610.095000.135812.90973.82170.0000
0.06160.1710000.135712.96203.89490.0000
0.06010.2615000.135712.87953.82250.0000
0.06660.3520000.135312.94813.88710.0000
0.06690.4325000.135212.82843.82830.0000
0.06650.5230000.135112.82033.78330.0000
0.06490.6135000.134912.80983.78240.0000
0.06070.6940000.134712.81103.81050.0000
0.06360.7845000.134512.79943.78930.0000
0.0630.8750000.134212.83193.80840.0000
0.05890.9555000.134112.88073.85510.0000
0.07341.0460000.134112.76913.76040.0000
0.05771.1365000.134012.76453.76020.0000
0.0521.2170000.134012.76103.76550.0000
0.06261.375000.133912.76573.75930.0000
0.06171.3980000.133812.79123.82680.0000
0.0631.4785000.133712.73433.75730.0000
0.06681.5690000.133612.73083.71980.0000
0.06341.6595000.133512.72153.74000.0000
0.06041.73100000.133312.71923.75150.0000
0.07071.82105000.133312.70523.75680.0000
0.06391.91110000.133212.69833.76170.0000
0.06171.99115000.133112.69363.74020.0000
0.06012.08120000.133012.69013.75860.0000
0.06322.17125000.133012.67853.72790.0000
0.06262.25130000.133012.68083.73330.0000
0.0662.34135000.132912.67043.75120.0000
0.06742.42140000.132912.65993.73840.0000
0.06372.51145000.132912.67973.74280.0000
0.06412.6150000.132912.67503.73050.0000

Framework versions

  • —Transformers 4.36.0.dev0
  • —Pytorch 2.1.1+cu121
  • —Datasets 2.15.0
  • —Tokenizers 0.15.0