You can deploy this model and start earning money today!

hsethu/
results

Name: results
Rating: 2.5 (10 reviews)

generated_from_trainer

ArtFair/diarizers_dataset_70-15-15

pyannote/segmentation-3.0

finetune

mit

Views

No views yet

results

This model is a fine-tuned version of pyannote/segmentation-3.0 on the ArtFair/diarizers_dataset_70-15-15 default dataset. It achieves the following results on the evaluation set:

Loss: 0.3941
Der: 0.2887
False Alarm: 0.1590
Missed Detection: 0.1025
Confusion: 0.0272

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: 0.001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Der	False Alarm	Missed Detection	Confusion
0.4009	1.0	747	0.4264	0.3191	0.1921	0.0979	0.0291
0.3626	2.0	1494	0.4017	0.3027	0.1664	0.1085	0.0278
0.3527	3.0	2241	0.4077	0.2972	0.1354	0.1347	0.0271
0.3303	4.0	2988	0.3933	0.2867	0.1506	0.1083	0.0277
0.3312	5.0	3735	0.3941	0.2887	0.1590	0.1025	0.0272

Framework versions

Transformers 4.37.2
Pytorch 2.4.1+cu121
Datasets 2.17.0
Tokenizers 0.15.2

hsethu/results

results

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hsethu/
results