Whisper Small yo - harcuracy model

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

  • Loss: 1.2762
  • Wer: 75.3382

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • 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
  • training_steps: 1500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1066 5.5556 500 0.9370 76.7003
0.0053 11.1111 1000 1.1919 74.9571
0.0012 16.6667 1500 1.2762 75.3382

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.4.0
  • Datasets 3.2.0
  • Tokenizers 0.21.0
Downloads last month
113
Safetensors
Model size
242M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Harcuracy/yoruba_medical_asr

Finetuned
(2220)
this model

Dataset used to train Harcuracy/yoruba_medical_asr

Evaluation results