README.md

metadata

library_name: transformers
language:
  - ps
base_model: ihanif/whisper-small-tunning-v2
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper Small PS - CV20-1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          args: 'config: ps, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 89.79300499643112

Whisper Small PS - CV20-1

This model is a fine-tuned version of ihanif/whisper-small-tunning-v2 on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.6103
• Wer Ortho: 91.8037
• Wer: 89.7930

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: 5e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• 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_ratio: 0.1
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
2.6485	1.8868	100	0.6103	91.8037	89.7930

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0