README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - physician_dictation_gpt_4_turbo
metrics:
  - wer
model-index:
  - name: Whisper Large v3 Physician Dictation GPT 4 turbo
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Physician Dictation GPT 4 Turbo
          type: physician_dictation_gpt_4_turbo
          config: default
          split: None
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 4.8915240533620805

Whisper Large v3 Physician Dictation GPT 4 turbo

This model is a fine-tuned version of openai/whisper-medium on the Physician Dictation GPT 4 Turbo dataset. It achieves the following results on the evaluation set:

• Loss: 0.1358
• Wer: 4.8915

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0039	7.9365	1000	0.1131	5.1925
0.001	15.8730	2000	0.1258	5.0712
0.0001	23.8095	3000	0.1329	4.9364
0.0001	31.7460	4000	0.1358	4.8915

Framework versions

• Transformers 4.40.2
• Pytorch 2.0.1+cu117
• Datasets 2.19.1
• Tokenizers 0.19.1