CoolFace
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simpragma/breeze-listen-dsw-base-kn

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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Breeze DSW Kannada - base

This model is a fine-tuned version of openai/whisper-base on the google/fleurs kn_in dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2258
  • —Wer: 30.6127

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: 1e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 16
  • —seed: 42
  • —distributed_type: multi-GPU
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —training_steps: 1000
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.71961.031000.516655.2130
0.27692.062000.253236.1594
0.18964.023000.216732.7298
0.13845.044000.203731.8356
0.10997.05000.203031.0560
0.07078.036000.215331.2453
0.0529.067000.225830.6127
0.037511.028000.241331.2204
0.025612.059000.250731.0635
0.024514.0110000.254931.1059

Framework versions

  • —Transformers 4.37.0.dev0
  • —Pytorch 2.1.2+cu121
  • —Datasets 2.16.2.dev0
  • —Tokenizers 0.15.0