speaker-segmentation-fine-tuned-datasetID-hugging_2_4_updated_01
This model is a fine-tuned version of pyannote/speaker-diarization-3.1 on the speaker-segmentation dataset. It achieves the following results on the evaluation set:
- Loss: 0.3877
- Model Preparation Time: 0.0041
- Der: 0.1275
- False Alarm: 0.0211
- Missed Detection: 0.0097
- Confusion: 0.0968
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
---|---|---|---|---|---|---|---|---|
0.5397 | 1.0 | 285 | 0.5425 | 0.0041 | 0.1807 | 0.0266 | 0.0139 | 0.1402 |
0.4678 | 2.0 | 570 | 0.4776 | 0.0041 | 0.1626 | 0.0221 | 0.0123 | 0.1283 |
0.4275 | 3.0 | 855 | 0.4479 | 0.0041 | 0.1488 | 0.0218 | 0.0103 | 0.1168 |
0.4065 | 4.0 | 1140 | 0.4242 | 0.0041 | 0.1416 | 0.0213 | 0.0103 | 0.1100 |
0.4065 | 5.0 | 1425 | 0.4137 | 0.0041 | 0.1374 | 0.0215 | 0.0101 | 0.1058 |
0.3939 | 6.0 | 1710 | 0.4140 | 0.0041 | 0.1373 | 0.0211 | 0.0102 | 0.1060 |
0.3581 | 7.0 | 1995 | 0.3972 | 0.0041 | 0.1328 | 0.0219 | 0.0094 | 0.1015 |
0.3589 | 8.0 | 2280 | 0.3983 | 0.0041 | 0.1327 | 0.0214 | 0.0099 | 0.1015 |
0.3575 | 9.0 | 2565 | 0.3969 | 0.0041 | 0.1318 | 0.0213 | 0.0097 | 0.1008 |
0.3639 | 10.0 | 2850 | 0.3899 | 0.0041 | 0.1273 | 0.0211 | 0.0097 | 0.0965 |
0.3417 | 11.0 | 3135 | 0.3891 | 0.0041 | 0.1284 | 0.0210 | 0.0098 | 0.0976 |
0.3475 | 12.0 | 3420 | 0.3898 | 0.0041 | 0.1278 | 0.0211 | 0.0097 | 0.0970 |
0.3212 | 13.0 | 3705 | 0.3899 | 0.0041 | 0.1280 | 0.0211 | 0.0097 | 0.0973 |
0.3384 | 14.0 | 3990 | 0.3885 | 0.0041 | 0.1277 | 0.0211 | 0.0097 | 0.0969 |
0.3258 | 15.0 | 4275 | 0.3877 | 0.0041 | 0.1275 | 0.0211 | 0.0097 | 0.0968 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for whitneyten/pydiarize-Dataset-2_4-update_01
Base model
pyannote/speaker-diarization-3.1