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Whisper Small Greek - Robust

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 el dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3605
  • Wer: 24.5264

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2223 2.35 500 0.4403 37.9922
0.0908 4.69 1000 0.4041 35.6519
0.0465 7.04 1500 0.4189 34.3053
0.0168 9.39 2000 0.3972 29.9127
0.0118 11.74 2500 0.4043 28.9933
0.0053 14.08 3000 0.3968 28.5940
0.0032 16.43 3500 0.3664 25.6779
0.0009 18.78 4000 0.3665 26.2444
0.0003 21.13 4500 0.3620 25.2879
0.0004 23.47 5000 0.3570 24.8607

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train ALM/whisper-el-small-augmented

Evaluation results