whisper_finetune

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Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.5896
• eval_wil: 42.8626
• eval_runtime: 1949.885
• eval_samples_per_second: 5.129
• eval_steps_per_second: 0.641
• epoch: 0.05
• step: 24000

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: 500000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.29.0.dev0
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3