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iFaz/whisper-SER-base-v1

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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whisper-SER-base-v1

This model is a fine-tuned version of openai/whisper-base on the WhisperCompatibleSERbenchmark(Not trainaugmented) dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.8757
  • —Wer: 105.4509

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: 1
  • —seed: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —training_steps: 6000
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.17612.445010000.562548.9594
0.07964.890020000.590587.2151
0.02017.335030000.7191125.5203
0.00549.780040000.7985127.7998
0.001212.224950000.8611108.0278
0.000814.669960000.8757105.4509

Framework versions

  • —Transformers 4.48.0
  • —Pytorch 2.5.1+cu121
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0