metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - yashtiwari/PaulMooney-Medical-ASR-Data
metrics:
  - wer
model-index:
  - name: Whisper Medium Medical
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Medical ASR
          type: yashtiwari/PaulMooney-Medical-ASR-Data
        metrics:
          - name: Wer
            type: wer
            value: 12.406468742457157

Whisper Medium Medical

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

Loss: 0.0995
Wer: 12.4065

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.7532	0.1357	100	0.2695	13.0099
0.2155	0.2714	200	0.2053	9.8238
0.2392	0.4071	300	0.1567	8.9549
0.151	0.5427	400	0.1159	6.9273
0.1439	0.6784	500	0.0995	12.4065

Framework versions

Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0