whisper-large-v2-lv / README.md
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metadata
language:
  - lv
license: apache-2.0
tags:
  - whisper-event
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Large-v2 Latvian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 lv
          type: mozilla-foundation/common_voice_11_0
          config: lv
          split: test
          args: lv
        metrics:
          - name: Wer
            type: wer
            value: 27.47628083491461

Whisper Large-v2 Latvian

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

  • Loss: 0.3179
  • Wer: 27.4763

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: 3e-07
  • train_batch_size: 64
  • eval_batch_size: 32
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 200
  • training_steps: 1500

Training results

Training Loss Epoch Step Validation Loss Wer
0.5148 3.01 200 0.4189 39.3454
0.3041 6.03 400 0.3335 29.5731
0.1961 9.04 600 0.3186 27.7799
0.2579 13.01 800 0.3167 27.5712
0.2034 16.03 1000 0.3179 27.4763
0.1478 19.04 1200 0.3193 27.5237
0.2169 23.01 1400 0.3198 27.5047

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 2.0.0.dev20221218+cu116
  • Datasets 2.7.1
  • Tokenizers 0.13.2