README.md

metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-base.en
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: 19.8989898989899

whisper-base.en

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

• Loss: 0.0213
• Wer: 19.8990

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: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0663	6.21	1000	0.0213	20.2020
0.0485	12.42	2000	0.0213	19.8990

Framework versions

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