amity-voice-segmentation-01

This model is a fine-tuned version of pyannote/segmentation-3.0 on the amityco/sample-voice-12-records dataset. It achieves the following results on the evaluation set:

• Loss: 0.1038
• Model Preparation Time: 0.0025
• Der: 0.0468
• False Alarm: 0.0280
• Missed Detection: 0.0188
• Confusion: 0.0

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: 8.5e-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: cosine
• num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Der	False Alarm	Missed Detection	Confusion
0.3728	1.0	54	0.1171	0.0025	0.0584	0.0207	0.0374	0.0003
0.3746	2.0	108	0.1112	0.0025	0.0522	0.0248	0.0272	0.0003
0.3479	3.0	162	0.1093	0.0025	0.0520	0.0258	0.0261	0.0
0.3252	4.0	216	0.1075	0.0025	0.0541	0.0285	0.0256	0.0
0.3675	5.0	270	0.1072	0.0025	0.0530	0.0291	0.0240	0.0
0.3123	6.0	324	0.1063	0.0025	0.0495	0.0288	0.0207	0.0
0.3033	7.0	378	0.1056	0.0025	0.0495	0.0285	0.0210	0.0
0.3105	8.0	432	0.1052	0.0025	0.0490	0.0280	0.0210	0.0
0.322	9.0	486	0.1045	0.0025	0.0482	0.0283	0.0199	0.0
0.3368	10.0	540	0.1040	0.0025	0.0485	0.0280	0.0205	0.0
0.2956	11.0	594	0.1039	0.0025	0.0476	0.0280	0.0197	0.0
0.2914	12.0	648	0.1041	0.0025	0.0476	0.0280	0.0197	0.0
0.2812	13.0	702	0.1039	0.0025	0.0476	0.0280	0.0197	0.0
0.3048	14.0	756	0.1040	0.0025	0.0474	0.0280	0.0194	0.0
0.283	15.0	810	0.1039	0.0025	0.0471	0.0280	0.0191	0.0
0.2952	16.0	864	0.1038	0.0025	0.0468	0.0280	0.0188	0.0
0.3061	17.0	918	0.1038	0.0025	0.0468	0.0280	0.0188	0.0
0.3122	18.0	972	0.1038	0.0025	0.0468	0.0280	0.0188	0.0
0.2941	19.0	1026	0.1038	0.0025	0.0468	0.0280	0.0188	0.0
0.2782	20.0	1080	0.1038	0.0025	0.0468	0.0280	0.0188	0.0

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1