whisper-large-v2-lv / README.md
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metadata
language:
  - lv
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
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
          type: mozilla-foundation/common_voice_11_0
          config: lv
          split: test
          args: lv
        metrics:
          - name: Wer
            type: wer
            value: 17.77988614800759

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: 0.2634
  • Wer: 17.7799

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-06
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer
0.2124 3.02 200 0.2485 18.4061
0.0704 6.05 400 0.2634 17.7799
0.0379 10.01 600 0.3103 17.8178
0.0228 13.03 800 0.3555 18.4061
0.0139 16.06 1000 0.3733 18.4535

Framework versions

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