whisper-medium-swagen-combined-10hrs-model

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

  • Loss: 0.4674
  • Wer: 0.3075

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.6418 0.2385 200 0.8312 0.4835
1.9381 0.4769 400 0.6574 0.4050
1.7528 0.7154 600 0.5706 0.3545
1.7421 0.9538 800 0.5140 0.3504
0.9259 1.1931 1000 0.5175 0.3262
0.8254 1.4316 1200 0.4978 0.3096
0.9616 1.6700 1400 0.4755 0.2999
0.7893 1.9085 1600 0.4674 0.3075
0.3547 2.1478 1800 0.4848 0.3158
0.3568 2.3863 2000 0.4913 0.2616
0.3759 2.6247 2200 0.4685 0.3104

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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Evaluation results