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pydiarize-Dataset-2_4-updated_03
whitneyten/pydiarize-Dataset-2_4-updated_03
pydiarize-Dataset-2_4-updated_03 is a machine learning model from whitneyten. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- pyannet
- Access
- Public
- Created
- Apr 16, 2025
- Updated
- Apr 16, 2025
- SHA
- 71d64bdc
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
speaker-segmentation-fine-tuned-datasetID-hugging_2_4_updated_03
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: 0.3830
- Model Preparation Time: 0.0032
- Der: 0.1285
- False Alarm: 0.0204
- Missed Detection: 0.0113
- 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: 0.0003
- 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: 0.15
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|---|
| 0.5423 | 1.0 | 400 | 0.5831 | 0.0032 | 0.1971 | 0.0254 | 0.0205 | 0.1511 |
| 0.4998 | 2.0 | 800 | 0.5031 | 0.0032 | 0.1721 | 0.0219 | 0.0149 | 0.1353 |
| 0.4588 | 3.0 | 1200 | 0.4654 | 0.0032 | 0.1577 | 0.0206 | 0.0134 | 0.1237 |
| 0.4467 | 4.0 | 1600 | 0.4401 | 0.0032 | 0.1511 | 0.0202 | 0.0130 | 0.1179 |
| 0.4192 | 5.0 | 2000 | 0.4276 | 0.0032 | 0.1432 | 0.0205 | 0.0122 | 0.1105 |
| 0.3991 | 6.0 | 2400 | 0.4157 | 0.0032 | 0.1413 | 0.0205 | 0.0118 | 0.1090 |
| 0.4042 | 7.0 | 2800 | 0.4016 | 0.0032 | 0.1355 | 0.0207 | 0.0114 | 0.1034 |
| 0.3972 | 8.0 | 3200 | 0.3959 | 0.0032 | 0.1330 | 0.0205 | 0.0113 | 0.1012 |
| 0.4001 | 9.0 | 3600 | 0.3914 | 0.0032 | 0.1324 | 0.0204 | 0.0114 | 0.1006 |
| 0.3733 | 10.0 | 4000 | 0.3892 | 0.0032 | 0.1310 | 0.0204 | 0.0114 | 0.0992 |
| 0.3835 | 11.0 | 4400 | 0.3855 | 0.0032 | 0.1300 | 0.0204 | 0.0113 | 0.0983 |
| 0.3716 | 12.0 | 4800 | 0.3859 | 0.0032 | 0.1293 | 0.0206 | 0.0111 | 0.0976 |
| 0.3655 | 13.0 | 5200 | 0.3836 | 0.0032 | 0.1286 | 0.0204 | 0.0113 | 0.0969 |
| 0.3743 | 14.0 | 5600 | 0.3833 | 0.0032 | 0.1284 | 0.0204 | 0.0113 | 0.0967 |
| 0.3592 | 15.0 | 6000 | 0.3830 | 0.0032 | 0.1285 | 0.0204 | 0.0113 | 0.0968 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Library
- transformers
- Type
- pyannet
- License
- mit
- Languages
- id
- Created
- Apr 16, 2025
- Updated
- Apr 16, 2025