metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-small.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: 1.8114259173246632

English Whisper Model

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

Loss: 0.0562
Wer: 1.8114

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
0.0142	5.0505	500	0.0464	2.3223
0.0014	10.1010	1000	0.0540	1.7882
0.0004	15.1515	1500	0.0562	1.8114

Framework versions

Transformers 4.42.4
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1