README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
  - generated_from_trainer
datasets:
  - Dev372/Medical_STT_Dataset_1.0
metrics:
  - wer
model-index:
  - name: English Whisper Model
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Medical
          type: Dev372/Medical_STT_Dataset_1.0
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 6.200650255457501

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: 0.1018
• Wer: 6.2007

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: 18
• 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
0.0554	5.0505	500	0.0921	5.2253
0.0044	10.1010	1000	0.0996	5.8059
0.0015	15.1515	1500	0.1018	6.2007

Framework versions

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