README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - custom_dataset
metrics:
  - wer
model-index:
  - name: Finetuned_whisper_tiny
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Dev372/Cardiology_Medical_STT_Dataset_split
          type: custom_dataset
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 2.4311183144246353

Finetuned_whisper_tiny

This model is a fine-tuned version of openai/whisper-tiny on the Dev372/Cardiology_Medical_STT_Dataset_split dataset. It achieves the following results on the evaluation set:

• Loss: 0.0460
• Wer: 2.4311

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: 15
• 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
0.0045	6.0976	500	0.0424	2.4311
0.0008	12.1951	1000	0.0446	2.4311
0.0006	18.2927	1500	0.0460	2.4311

Framework versions

• Transformers 4.42.4
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1