iFaz/whisper-base-SER-v5_2

whisper-base-SER-v5_1

This fine-tune is corrupted (because i used mistakenly only 100 rows for training😑😑😑

) This model is a fine-tuned version of openai/whisper-base on the Whisper_Compatible_SER_benchmark(Not train_augmented) dataset. It achieves the following results on the evaluation set:

• Loss: 0.3675
• Wer: 236.0

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: 32
• 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_steps: 500
• training_steps: 6000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0004	250.0	1000	0.2744	665.0
0.0001	500.0	2000	0.3142	413.0
0.0	750.0	3000	0.3356	239.0
0.0	1000.0	4000	0.3451	239.0
0.0	1250.0	5000	0.3657	236.0
0.0	1500.0	6000	0.3675	236.0

Framework versions

• Transformers 4.48.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0