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whisper-small-he-3

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
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whisper-small-he-3 / README.md
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metadata
language:
  - he
license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - ivrit-ai/whisper-training
metrics:
  - wer
model-index:
  - name: Whisper Small Hebrew
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ivrit-ai/whisper-training
          type: ivrit-ai/whisper-training
          args: 'config: he, split: train'
        metrics:
          - name: Wer
            type: wer
            value: 40.6755346896192

Whisper Small Hebrew

This model is a fine-tuned version of openai/whisper-small on the ivrit-ai/whisper-training dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4241
  • Wer: 40.6755

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
  • 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: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4946 0.13 500 0.4572 46.4463
0.4629 0.25 1000 0.4492 43.7663
0.4067 0.38 1500 0.4337 42.6317
0.3663 0.5 2000 0.3892 41.8427
0.3857 0.63 2500 0.4017 40.7473
0.3795 0.75 3000 0.4011 39.4823
0.368 0.88 3500 0.3967 39.9778
0.2353 1.01 4000 0.3801 38.3281
0.2405 1.13 4500 0.4062 41.5428
0.2512 1.26 5000 0.3975 38.6215
0.2433 1.38 5500 0.4035 38.5824
0.2368 1.51 6000 0.3983 37.8652
0.2592 1.63 6500 0.4184 39.1041
0.2629 1.76 7000 0.4000 39.5475
0.2318 1.88 7500 0.4012 39.1954
0.1658 2.01 8000 0.3941 39.1367
0.1546 2.14 8500 0.4226 39.8865
0.1665 2.26 9000 0.4295 40.9755
0.1642 2.39 9500 0.4314 41.1255
0.1694 2.51 10000 0.4241 40.6755

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2