README.md

metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - PolyAI/minds14
metrics:
  - wer
model-index:
  - name: Whisper Tiny en-US - janater123456
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Minds14
          type: PolyAI/minds14
        metrics:
          - name: Wer
            type: wer
            value: 0.33234946871310506

Whisper Tiny en-US - janater123456

This model is a fine-tuned version of openai/whisper-tiny on the Minds14 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5693
• Wer Ortho: 0.3418
• Wer: 0.3323

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: 16
• seed: 42
• optimizer: Use OptimizerNames.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
• lr_scheduler_warmup_steps: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0092	8.9286	500	0.5693	0.3418	0.3323

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu124
• Tokenizers 0.21.0