Whisper medium pt jwlang - Michel Mesquita

This model is a fine-tuned version of openai/whisper-medium on the jwlang 1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6361
  • Wer: 18.7271

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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0038 14.0845 1000 0.5291 20.3182
0.0001 28.1690 2000 0.6034 18.9718
0.0 42.2535 3000 0.6277 19.0942
0.0 56.3380 4000 0.6361 18.7271

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Dataset used to train M2LabOrg/whisper-medium-pt-jwlang

Evaluation results