README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
  - nyansapo_ai-asr-leaderboard
  - generated_from_trainer
datasets:
  - NyansapoAI/azure-dataset
metrics:
  - wer
model-index:
  - name: whisper-tiny.en
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Azure-dataset
          type: NyansapoAI/azure-dataset
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 8.886971527178602

whisper-tiny.en

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

• Loss: 0.0691
• Wer: 8.8870

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: 250
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.2834	1.38	250	0.6457	19.0682
0.3634	2.76	500	0.0896	7.5065
0.216	4.14	750	0.0727	6.8162
0.1824	5.52	1000	0.0691	8.8870

Framework versions

• Transformers 4.39.1
• Pytorch 2.2.1
• Datasets 2.18.0
• Tokenizers 0.15.2