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:
+- diarizers-community/callhome
+model-index:
+- name: speaker-segmentation-fine-tuned-callhome-spa
+  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-spa
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome spa dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5198
+- Der: 0.1745
+- False Alarm: 0.0739
+- Missed Detection: 0.0687
+- Confusion: 0.0319
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.655         | 1.0   | 382  | 0.5330          | 0.1799 | 0.0680      | 0.0756           | 0.0364    |
+| 0.6293        | 2.0   | 764  | 0.5216          | 0.1747 | 0.0662      | 0.0746           | 0.0339    |
+| 0.6145        | 3.0   | 1146 | 0.5244          | 0.1770 | 0.0759      | 0.0686           | 0.0325    |
+| 0.5956        | 4.0   | 1528 | 0.5185          | 0.1734 | 0.0732      | 0.0687           | 0.0315    |
+| 0.5989        | 5.0   | 1910 | 0.5198          | 0.1745 | 0.0739      | 0.0687           | 0.0319    |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:66172693b8a5ed7b2a01e15405d44c7a7c4df0805b2f9a42aacb3e3481b0f8fc
+oid sha256:b8f025903a50d90c227ad6e86c2855ad05b3f765739de9c4ea633dd058c22da0
 size 5899124