README.md

metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
  - generated_from_trainer
datasets:
  - Dev372/Medical_STT_Dataset_1.1
metrics:
  - wer
model-index:
  - name: Whisper Medium
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Medical STT
          type: Dev372/Medical_STT_Dataset_1.1
        metrics:
          - name: Wer
            type: wer
            value: 3.2511210762331837

Whisper Medium

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

• Loss: 0.0977
• Wer Ortho: 5.4215
• Wer: 3.2511

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0481	1.2563	500	0.0977	5.4215	3.2511

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0