README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
  - generated_from_trainer
datasets:
  - HarshDev_custom_dataset
metrics:
  - wer
model-index:
  - name: English Whisper Model
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Medical
          type: HarshDev_custom_dataset
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 2.3778501628664497

English Whisper Model

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

• Loss: 0.0006
• Wer: 2.3779

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: 15
• 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: 1500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0264	4.9020	500	0.0109	1.6205
0.0012	9.8039	1000	0.0009	2.2801
0.0007	14.7059	1500	0.0006	2.3779

Framework versions

• Transformers 4.42.4
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1