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Whisper Large-v2 Latvian

This model is a fine-tuned version of p4b/whisper-large-v2-lv on the mozilla-foundation/common_voice_11_0 lv dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2593
  • Wer: 19.9715

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-07
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 900

Training results

Training Loss Epoch Step Validation Loss Wer
0.7919 3.03 200 0.2793 22.5806
0.4409 6.05 400 0.2651 20.6072
0.4393 10.01 600 0.2600 20.0664
0.4975 13.04 800 0.2593 19.9715

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 2.0.0.dev20221218+cu116
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train p4b/whisper-large-v2-lv

Evaluation results