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metadata
language:
  - fi
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Large v3 Fine-Tuned Finnish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 13.0
          type: mozilla-foundation/common_voice_13_0
          config: fi
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 23.016749493833977

Whisper Large v3 Fine-Tuned Finnish

This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3344
  • Wer: 23.0167

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 50
  • training_steps: 800
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5817 0.42 50 0.4090 37.5023
0.4669 0.84 100 0.4374 35.8274
0.3154 1.26 150 0.4848 39.0484
0.2192 1.68 200 0.4313 34.6954
0.1985 2.1 250 0.4346 34.5205
0.1125 2.52 300 0.4307 32.8640
0.1039 2.94 350 0.4278 31.3271
0.067 3.36 400 0.4043 33.5542
0.0577 3.78 450 0.3911 40.7050
0.0461 4.2 500 0.3966 30.4712
0.0264 4.62 550 0.3630 27.2041
0.0204 5.04 600 0.3632 26.0353
0.0092 5.46 650 0.3448 24.4156
0.006 5.88 700 0.3284 23.9278
0.002 6.3 750 0.3334 23.2836
0.0019 6.72 800 0.3344 23.0167

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.0.1
  • Datasets 2.16.1
  • Tokenizers 0.15.0