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/ami
+model-index:
+- name: speaker-segmentation-fine-tuned-ami-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-ami-2
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/ami ihm dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3764
+- Der: 0.1401
+- False Alarm: 0.0503
+- Missed Detection: 0.0575
+- Confusion: 0.0323
+
+## 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: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.4149        | 1.0   | 1427  | 0.3607          | 0.1407 | 0.0492      | 0.0593           | 0.0323    |
+| 0.3915        | 2.0   | 2854  | 0.3684          | 0.1422 | 0.0460      | 0.0621           | 0.0340    |
+| 0.3748        | 3.0   | 4281  | 0.3730          | 0.1419 | 0.0530      | 0.0570           | 0.0318    |
+| 0.3778        | 4.0   | 5708  | 0.3649          | 0.1409 | 0.0472      | 0.0611           | 0.0326    |
+| 0.3565        | 5.0   | 7135  | 0.3723          | 0.1415 | 0.0501      | 0.0591           | 0.0324    |
+| 0.3566        | 6.0   | 8562  | 0.3740          | 0.1406 | 0.0499      | 0.0584           | 0.0323    |
+| 0.3534        | 7.0   | 9989  | 0.3736          | 0.1399 | 0.0493      | 0.0581           | 0.0325    |
+| 0.3418        | 8.0   | 11416 | 0.3744          | 0.1397 | 0.0500      | 0.0577           | 0.0321    |
+| 0.3388        | 9.0   | 12843 | 0.3777          | 0.1403 | 0.0505      | 0.0574           | 0.0324    |
+| 0.346         | 10.0  | 14270 | 0.3764          | 0.1401 | 0.0503      | 0.0575           | 0.0323    |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.19.1

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