End of training

README.md

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+---
+library_name: transformers
+language:
+- fr
+license: mit
+base_model: pyannote/segmentation-3.0
+tags:
+- speaker-diarization
+- speaker-segmentation
+- generated_from_trainer
+datasets:
+- MPF
+model-index:
+- name: speaker-segmentation-ft-mpf
+  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-ft-mpf
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the MPF dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8806
+- Model Preparation Time: 0.004
+- Der: 0.3412
+- False Alarm: 0.0953
+- Missed Detection: 0.1247
+- Confusion: 0.1211
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Model Preparation Time | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.9823        | 1.0   | 1302  | 0.9267          | 0.004                  | 0.3729 | 0.0896      | 0.1466           | 0.1367    |
+| 0.9422        | 2.0   | 2604  | 0.9247          | 0.004                  | 0.3695 | 0.0991      | 0.1282           | 0.1422    |
+| 0.915         | 3.0   | 3906  | 0.8984          | 0.004                  | 0.3549 | 0.0878      | 0.1397           | 0.1273    |
+| 0.8706        | 4.0   | 5208  | 0.9055          | 0.004                  | 0.3543 | 0.1036      | 0.1171           | 0.1336    |
+| 0.8511        | 5.0   | 6510  | 0.8776          | 0.004                  | 0.3424 | 0.0932      | 0.1279           | 0.1213    |
+| 0.834         | 6.0   | 7812  | 0.8896          | 0.004                  | 0.3485 | 0.1004      | 0.1220           | 0.1261    |
+| 0.8505        | 7.0   | 9114  | 0.8777          | 0.004                  | 0.3418 | 0.0959      | 0.1260           | 0.1199    |
+| 0.8452        | 8.0   | 10416 | 0.8802          | 0.004                  | 0.3430 | 0.0975      | 0.1246           | 0.1209    |
+| 0.837         | 9.0   | 11718 | 0.8792          | 0.004                  | 0.3407 | 0.0950      | 0.1247           | 0.1211    |
+| 0.8459        | 10.0  | 13020 | 0.8806          | 0.004                  | 0.3412 | 0.0953      | 0.1247           | 0.1211    |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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