whisper_finetune_ksponspeech_partial

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Whisper large-v2, KsponSpeech Partial 5 epochs

This model is a fine-tuned version of openai/whisper-large-v2 on the KsponSpeech dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0150
• eval_wer: 25.4322
• eval_runtime: 1298.665
• eval_samples_per_second: 0.689
• eval_steps_per_second: 0.689
• epoch: 5.07
• step: 300

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 300

Framework versions

• Transformers 4.31.0
• Pytorch 1.12.1+cu116
• Datasets 2.14.0
• Tokenizers 0.12.1