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dts_ESLO.06.05.25_exp.ft.dia.1.A_mdl.no1
Rziane/dts_ESLO.06.05.25_exp.ft.dia.1.A_mdl.no1
dts_ESLO.06.05.25_exp.ft.dia.1.A_mdl.no1 is a machine learning model from Rziane. 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
- May 18, 2025
- Updated
- May 18, 2025
- SHA
- b7ab592b
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. -->
dts_ESLO.06.05.25_exp.ft.dia.1.A_mdl.no1
This model is a fine-tuned version of pyannote/segmentation-3.0 on the CAENNAIS dataset. It achieves the following results on the evaluation set:
- Loss: 0.7479
- Model Preparation Time: 0.0044
- Der: 0.4638
- False Alarm: 0.1470
- Missed Detection: 0.2281
- Confusion: 0.0888
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|---|
| 0.8676 | 1.0 | 270 | 0.7954 | 0.0044 | 0.5104 | 0.1441 | 0.2546 | 0.1117 |
| 0.8147 | 2.0 | 540 | 0.7855 | 0.0044 | 0.5000 | 0.1319 | 0.2714 | 0.0967 |
| 0.8085 | 3.0 | 810 | 0.7573 | 0.0044 | 0.4754 | 0.1503 | 0.2216 | 0.1036 |
| 0.7639 | 4.0 | 1080 | 0.7556 | 0.0044 | 0.4719 | 0.1445 | 0.2282 | 0.0993 |
| 0.7599 | 5.0 | 1350 | 0.7472 | 0.0044 | 0.4685 | 0.1595 | 0.2048 | 0.1041 |
| 0.7611 | 6.0 | 1620 | 0.7520 | 0.0044 | 0.4670 | 0.1463 | 0.2260 | 0.0947 |
| 0.7299 | 7.0 | 1890 | 0.7917 | 0.0044 | 0.4768 | 0.1359 | 0.2535 | 0.0874 |
| 0.7409 | 8.0 | 2160 | 0.7331 | 0.0044 | 0.4661 | 0.1432 | 0.2254 | 0.0974 |
| 0.7153 | 9.0 | 2430 | 0.7479 | 0.0044 | 0.4662 | 0.1583 | 0.2068 | 0.1010 |
| 0.7247 | 10.0 | 2700 | 0.7446 | 0.0044 | 0.4619 | 0.1527 | 0.2192 | 0.0899 |
| 0.7187 | 11.0 | 2970 | 0.7425 | 0.0044 | 0.4637 | 0.1427 | 0.2328 | 0.0882 |
| 0.7259 | 12.0 | 3240 | 0.7391 | 0.0044 | 0.4601 | 0.1453 | 0.2278 | 0.0870 |
| 0.6628 | 13.0 | 3510 | 0.7496 | 0.0044 | 0.4610 | 0.1486 | 0.2250 | 0.0874 |
| 0.6894 | 14.0 | 3780 | 0.7429 | 0.0044 | 0.4598 | 0.1428 | 0.2312 | 0.0858 |
| 0.681 | 15.0 | 4050 | 0.7454 | 0.0044 | 0.4603 | 0.1502 | 0.2193 | 0.0907 |
| 0.6821 | 16.0 | 4320 | 0.7409 | 0.0044 | 0.4621 | 0.1496 | 0.2213 | 0.0911 |
| 0.6868 | 17.0 | 4590 | 0.7472 | 0.0044 | 0.4647 | 0.1478 | 0.2263 | 0.0907 |
| 0.6821 | 18.0 | 4860 | 0.7472 | 0.0044 | 0.4628 | 0.1473 | 0.2268 | 0.0887 |
| 0.6987 | 19.0 | 5130 | 0.7477 | 0.0044 | 0.4637 | 0.1466 | 0.2287 | 0.0884 |
| 0.7158 | 20.0 | 5400 | 0.7479 | 0.0044 | 0.4638 | 0.1470 | 0.2281 | 0.0888 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
- Library
- transformers
- Type
- pyannet
- License
- mit
- Languages
- fr
- Created
- May 18, 2025
- Updated
- May 18, 2025