whisper-lg-el-intlv-xs

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2913
  • Wer: 9.8997

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: 3.5e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0311 2.49 1000 0.1809 10.5498
0.0074 4.98 2000 0.2470 10.2805
0.0019 7.46 3000 0.3008 10.0297
0.0011 9.95 4000 0.2913 9.8997
0.0009 12.44 5000 0.3092 10.1876
0.0005 14.93 6000 0.3495 10.1969
0.0002 17.41 7000 0.3659 10.2526
0.0001 19.9 8000 0.3846 10.2619
0.0001 22.39 9000 0.3941 10.2897
0.0001 24.88 10000 0.3990 10.3269

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Datasets used to train farsipal/whisper-lg-el-intlv-xs

Evaluation results