End of training

README.md

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+---
+library_name: transformers
+language:
+- fr
+license: mit
+base_model: pyannote/speaker-diarization-3.1
+tags:
+- speaker-diarization
+- speaker-segmentation
+- generated_from_trainer
+datasets:
+- ESLO2
+model-index:
+- name: speaker-segmentation-fine-tuned_ESLO2
+  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-fine-tuned_ESLO2
+
+This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the ESLO2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0390
+- Model Preparation Time: 0.004
+- Der: 0.5468
+- False Alarm: 0.1928
+- Missed Detection: 0.2690
+- Confusion: 0.0849
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
+| 1.0681        | 1.0   | 686  | 1.0642          | 0.004                  | 0.5632 | 0.1931      | 0.2781           | 0.0921    |
+| 1.0147        | 2.0   | 1372 | 1.0523          | 0.004                  | 0.5551 | 0.1887      | 0.2772           | 0.0893    |
+| 1.0044        | 3.0   | 2058 | 1.0445          | 0.004                  | 0.5537 | 0.1887      | 0.2791           | 0.0859    |
+| 0.9801        | 4.0   | 2744 | 1.0352          | 0.004                  | 0.5464 | 0.1934      | 0.2677           | 0.0853    |
+| 0.9866        | 5.0   | 3430 | 1.0390          | 0.004                  | 0.5468 | 0.1928      | 0.2690           | 0.0849    |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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runs/Oct08_17-32-34_V301V-JGRCC1.campus.unicaen.fr/events.out.tfevents.1728401570.V301V-JGRCC1.campus.unicaen.fr

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