metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - srirama/dental
metrics:
  - wer
model-index:
  - name: Whisper Small - D Notes
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Sample Dental
          type: srirama/dental
          config: default
          split: None
          args: 'config: default, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 6.684121361466194

Whisper Small - D Notes

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

Loss: 0.0001
Wer: 6.6841

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: 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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0024	10.9890	1000	0.0010	7.0692
0.0002	21.9780	2000	0.0003	6.6687
0.0001	32.9670	3000	0.0001	6.6071
0.0001	43.9560	4000	0.0001	6.6841

Framework versions

Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1