End of training

README.md

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+---
+license: mit
+base_model: pyannote/segmentation-3.0
+tags:
+- speaker-diarization
+- speaker-segmentation
+- generated_from_trainer
+datasets:
+- diarizers-community/callhome
+model-index:
+- name: speaker-segmentation-fine-tuned-callhome-eng-2
+  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-callhome-eng-2
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome eng dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4666
+- Der: 0.1814
+- False Alarm: 0.0552
+- Missed Detection: 0.0739
+- Confusion: 0.0523
+
+## 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: 64
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.4548        | 1.0   | 181  | 0.4943          | 0.1966 | 0.0564      | 0.0811           | 0.0590    |
+| 0.4171        | 2.0   | 362  | 0.4845          | 0.1951 | 0.0644      | 0.0754           | 0.0552    |
+| 0.396         | 3.0   | 543  | 0.4633          | 0.1856 | 0.0502      | 0.0825           | 0.0529    |
+| 0.3856        | 4.0   | 724  | 0.4609          | 0.1843 | 0.0571      | 0.0739           | 0.0534    |
+| 0.3693        | 5.0   | 905  | 0.4639          | 0.1821 | 0.0531      | 0.0761           | 0.0528    |
+| 0.3634        | 6.0   | 1086 | 0.4610          | 0.1821 | 0.0588      | 0.0716           | 0.0517    |
+| 0.3655        | 7.0   | 1267 | 0.4638          | 0.1827 | 0.0566      | 0.0740           | 0.0521    |
+| 0.3608        | 8.0   | 1448 | 0.4603          | 0.1814 | 0.0567      | 0.0732           | 0.0515    |
+| 0.3545        | 9.0   | 1629 | 0.4645          | 0.1805 | 0.0530      | 0.0761           | 0.0514    |
+| 0.3508        | 10.0  | 1810 | 0.4666          | 0.1814 | 0.0552      | 0.0739           | 0.0523    |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.19.1

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