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-jpn
+  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-jpn
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome jpn dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7579
+- Der: 0.2246
+- False Alarm: 0.0481
+- Missed Detection: 0.1329
+- Confusion: 0.0437
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.5686        | 1.0   | 328  | 0.7818          | 0.2346 | 0.0479      | 0.1378           | 0.0489    |
+| 0.5307        | 2.0   | 656  | 0.7629          | 0.2278 | 0.0480      | 0.1359           | 0.0440    |
+| 0.5212        | 3.0   | 984  | 0.7597          | 0.2287 | 0.0512      | 0.1341           | 0.0435    |
+| 0.5155        | 4.0   | 1312 | 0.7562          | 0.2244 | 0.0502      | 0.1314           | 0.0427    |
+| 0.5053        | 5.0   | 1640 | 0.7579          | 0.2246 | 0.0481      | 0.1329           | 0.0437    |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul08_14-33-42_dcfc98c52455/events.out.tfevents.1720449548.dcfc98c52455.4687.0

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