End of training

README.md

@@ -0,0 +1,69 @@
+---
+license: mit
+base_model: pyannote/segmentation-3.0
+tags:
+- speaker-diarization
+- speaker-segmentation
+- generated_from_trainer
+datasets:
+- KMayanja/backup_uganda
+model-index:
+- name: speaker-segmentation-fine-tuned-backup-uganda
+  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-backup-uganda
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the KMayanja/backup_uganda default dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2271
+- Der: 0.0667
+- False Alarm: 0.0188
+- Missed Detection: 0.0260
+- Confusion: 0.0219
+
+## 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: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.1819        | 1.0   | 266  | 0.2174          | 0.0663 | 0.0186      | 0.0249           | 0.0228    |
+| 0.1659        | 2.0   | 532  | 0.2177          | 0.0669 | 0.0169      | 0.0278           | 0.0221    |
+| 0.1549        | 3.0   | 798  | 0.2170          | 0.0659 | 0.0181      | 0.0261           | 0.0217    |
+| 0.1535        | 4.0   | 1064 | 0.2222          | 0.0666 | 0.0195      | 0.0251           | 0.0220    |
+| 0.1541        | 5.0   | 1330 | 0.2271          | 0.0667 | 0.0188      | 0.0260           | 0.0219    |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7293e2f9a02d393fa3f8e616444e9cf9b80ad5e35493c4b631ff60da5fea9b34
+oid sha256:f119008bad05177673cf4ca8be601e18f4835bb012ee22e8a4cf31511fc7e644
 size 5899124