whisper-turbo-tr_All_datasets_finetune

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1497

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.1651	0.4869	1500	0.1745
0.158	0.9737	3000	0.1590
0.1391	1.4606	4500	0.1540
0.1509	1.9474	6000	0.1516
0.1387	2.4343	7500	0.1500
0.1428	2.9211	9000	0.1497

Framework versions

• PEFT 0.15.1
• Transformers 4.48.0
• Pytorch 2.5.1
• Datasets 3.0.0
• Tokenizers 0.21.1