whisper-large-v2-ft-cy-2606

This model is a fine-tuned version of openai/whisper-large-v2 on the DewiBrynJones/preprocessed-whisper-btb-cv-cvad-wlga-ca-2606 dataset.

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: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 32
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 500
• training_steps: 15000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.57.6
• Pytorch 2.12.0+cu130
• Datasets 5.0.0
• Tokenizers 0.22.2