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metadata
language:
  - el
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
  - automatic-speech-recognition
  - greek
datasets:
  - mozilla-foundation/common_voice_11_0,google/fleurs
metrics:
  - wer
model-index:
  - name: whisper-md-el-intlv-xs
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          args: 'config: el, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 11.36701337295691

whisper-md-el-intlv-xs

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

  • Loss: 0.4168
  • Wer: 11.3670

Model description

This model is trained over two interleaved datasets for the Greek language and is tested only on the common_voice_11_0 test split.

Intended uses & limitations

It is intended for transcription in Greek

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 8e-06
  • train_batch_size: 32
  • 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: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0251 2.49 1000 0.2216 12.5836
0.0051 4.98 2000 0.2874 12.2957
0.0015 7.46 3000 0.3281 11.9056
0.0017 9.95 4000 0.3178 12.5929
0.0008 12.44 5000 0.3449 11.9799
0.0001 14.93 6000 0.3638 11.7106
0.0001 17.41 7000 0.3910 11.4970
0.0 19.9 8000 0.4042 11.3949
0.0 22.39 9000 0.4129 11.4134
0.0 24.88 10000 0.4168 11.3670

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2