README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - nyansapo_ai-asr-leaderboard
  - generated_from_trainer
datasets:
  - NyansapoAI/azure-dataset
metrics:
  - wer
model-index:
  - name: whisper-base.en
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Azure-dataset
          type: NyansapoAI/azure-dataset
          config: default
          split: test
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 8.585858585858585

whisper-base.en

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

• Loss: 0.0237
• Wer: 8.5859

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: 2500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1945	3.11	500	0.0626	18.0808
0.0627	6.21	1000	0.0292	10.5051
0.0419	9.32	1500	0.0242	9.0909
0.0419	12.42	2000	0.0242	8.8889
0.0502	15.53	2500	0.0237	8.5859

Framework versions

• Transformers 4.33.0.dev0
• Pytorch 2.0.1
• Datasets 2.14.4
• Tokenizers 0.13.3