| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: speaker-segmentation-darija2 |
| results: [] |
| --- |
| |
| <!-- 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-darija2 |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3338 |
| - Model Preparation Time: 0.0061 |
| - Der: 0.1220 |
| - False Alarm: 0.0235 |
| - Missed Detection: 0.0296 |
| - Confusion: 0.0688 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - 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 |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 30 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion | |
| |:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:| |
| | 0.7164 | 1.0 | 683 | 0.8500 | 0.0061 | 0.2406 | 0.0365 | 0.0432 | 0.1609 | |
| | 0.6075 | 2.0 | 1366 | 0.6868 | 0.0061 | 0.2182 | 0.0361 | 0.0408 | 0.1413 | |
| | 0.5213 | 3.0 | 2049 | 0.5659 | 0.0061 | 0.1947 | 0.0329 | 0.0395 | 0.1224 | |
| | 0.4664 | 4.0 | 2732 | 0.5040 | 0.0061 | 0.1821 | 0.0306 | 0.0372 | 0.1143 | |
| | 0.411 | 5.0 | 3415 | 0.4678 | 0.0061 | 0.1738 | 0.0297 | 0.0355 | 0.1086 | |
| | 0.4205 | 6.0 | 4098 | 0.4503 | 0.0061 | 0.1682 | 0.0286 | 0.0348 | 0.1048 | |
| | 0.4133 | 7.0 | 4781 | 0.4330 | 0.0061 | 0.1629 | 0.0285 | 0.0336 | 0.1009 | |
| | 0.3936 | 8.0 | 5464 | 0.4191 | 0.0061 | 0.1579 | 0.0278 | 0.0329 | 0.0972 | |
| | 0.3799 | 9.0 | 6147 | 0.4080 | 0.0061 | 0.1529 | 0.0276 | 0.0323 | 0.0931 | |
| | 0.3557 | 10.0 | 6830 | 0.4007 | 0.0061 | 0.1500 | 0.0269 | 0.0317 | 0.0914 | |
| | 0.3564 | 11.0 | 7513 | 0.3915 | 0.0061 | 0.1465 | 0.0258 | 0.0319 | 0.0888 | |
| | 0.3658 | 12.0 | 8196 | 0.3853 | 0.0061 | 0.1433 | 0.0258 | 0.0314 | 0.0861 | |
| | 0.3606 | 13.0 | 8879 | 0.3784 | 0.0061 | 0.1408 | 0.0255 | 0.0311 | 0.0842 | |
| | 0.3685 | 14.0 | 9562 | 0.3739 | 0.0061 | 0.1390 | 0.0255 | 0.0308 | 0.0827 | |
| | 0.3364 | 15.0 | 10245 | 0.3706 | 0.0061 | 0.1378 | 0.0253 | 0.0306 | 0.0818 | |
| | 0.3436 | 16.0 | 10928 | 0.3698 | 0.0061 | 0.1369 | 0.0248 | 0.0307 | 0.0814 | |
| | 0.3339 | 17.0 | 11611 | 0.3636 | 0.0061 | 0.1353 | 0.0249 | 0.0304 | 0.0799 | |
| | 0.3416 | 18.0 | 12294 | 0.3615 | 0.0061 | 0.1343 | 0.0246 | 0.0304 | 0.0792 | |
| | 0.3396 | 19.0 | 12977 | 0.3593 | 0.0061 | 0.1337 | 0.0243 | 0.0305 | 0.0789 | |
| | 0.344 | 20.0 | 13660 | 0.3572 | 0.0061 | 0.1330 | 0.0243 | 0.0305 | 0.0782 | |
| | 0.3372 | 21.0 | 14343 | 0.3541 | 0.0061 | 0.1320 | 0.0245 | 0.0302 | 0.0773 | |
| | 0.3271 | 22.0 | 15026 | 0.3549 | 0.0061 | 0.1313 | 0.0242 | 0.0302 | 0.0768 | |
| | 0.3206 | 23.0 | 15709 | 0.3516 | 0.0061 | 0.1310 | 0.0243 | 0.0301 | 0.0766 | |
| | 0.3359 | 24.0 | 16392 | 0.3524 | 0.0061 | 0.1308 | 0.0242 | 0.0301 | 0.0765 | |
| | 0.322 | 25.0 | 17075 | 0.3512 | 0.0061 | 0.1304 | 0.0241 | 0.0301 | 0.0762 | |
| | 0.3169 | 26.0 | 17758 | 0.3507 | 0.0061 | 0.1301 | 0.0243 | 0.0300 | 0.0758 | |
| | 0.3351 | 27.0 | 18441 | 0.3508 | 0.0061 | 0.1300 | 0.0243 | 0.0299 | 0.0758 | |
| | 0.3221 | 28.0 | 19124 | 0.3501 | 0.0061 | 0.1300 | 0.0243 | 0.0299 | 0.0758 | |
| | 0.324 | 29.0 | 19807 | 0.3499 | 0.0061 | 0.1300 | 0.0243 | 0.0299 | 0.0758 | |
| | 0.3271 | 30.0 | 20490 | 0.3499 | 0.0061 | 0.1300 | 0.0243 | 0.0299 | 0.0758 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.57.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 4.4.2 |
| - Tokenizers 0.22.2 |
|
|
