Whisper Medium eu

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1067
  • Wer: 6.2269

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: 32
  • 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: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1766 0.3596 1000 0.1877 12.7130
0.1372 0.7192 2000 0.1370 8.7444
0.0634 1.0787 3000 0.1210 7.2108
0.0558 1.4383 4000 0.1119 6.5411
0.0631 1.7979 5000 0.1067 6.2269

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
Downloads last month
12
Safetensors
Model size
764M params
Tensor type
F32
·
Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for deepdml/whisper-medium-eu-cv17

Finetuned
(499)
this model

Dataset used to train deepdml/whisper-medium-eu-cv17

Evaluation results