adima_training_new_2

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

• Loss: 0.4923
• Accuracy: 0.8096
• F1: 0.7725
• Precision: 0.8067
• Recall: 0.7410
• Auc: 0.8745

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: 8
• 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: 100
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Accuracy	Auc	F1	Validation Loss	Precision	Recall
0.4959	1.0	1012	0.7664	0.8395	0.7056	0.5189	0.7833	0.6418
0.4136	2.0	2024	0.7890	0.8549	0.7295	0.5210	0.8271	0.6526
0.413	3.0	3036	0.4964	0.8008	0.7605	0.7994	0.7252	0.8650
0.4113	4.0	4048	0.5015	0.8066	0.7620	0.8222	0.7100	0.8706
0.3754	5.0	5060	0.4990	0.8113	0.7671	0.8306	0.7126	0.8738
0.3449	6.0	6072	0.4923	0.8096	0.7725	0.8067	0.7410	0.8745

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu126
• Datasets 3.6.0
• Tokenizers 0.21.1