metadata

library_name: peft
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
  - generated_from_trainer
model-index:
  - name: whisper-turbo-tr_All_datasets_finetune_4
    results: []

whisper-turbo-tr_All_datasets_finetune_4

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: 0.2189

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: 0.0003
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
0.1902	0.9186	1500	0.3348
0.097	1.8371	3000	0.2756
0.0284	2.7557	4500	0.2189

Framework versions

PEFT 0.15.1
Transformers 4.51.3
Pytorch 2.5.1
Datasets 3.0.0
Tokenizers 0.21.1