End of training

README.md

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+---
+library_name: transformers
+language:
+- bn
+license: mit
+base_model: pyannote/segmentation-3.0
+tags:
+- audio
+- speaker-diarization
+- bengali
+- pyannote
+- speech
+- generated_from_trainer
+datasets:
+- bengali-speaker-diarization
+model-index:
+- name: speaker-segmentation-bengali-optimized-conservative
+  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-bengali-optimized-conservative
+
+This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the bengali-speaker-diarization dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4778
+- Model Preparation Time: 0.0043
+- Der: 0.1599
+- False Alarm: 0.0403
+- Missed Detection: 0.0162
+- Confusion: 0.1034
+
+## 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: 0.0005
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.4209        | 1.0   | 254  | 0.4600          | 0.0043                 | 0.1574 | 0.0369      | 0.0185           | 0.1019    |
+| 0.391         | 2.0   | 508  | 0.4628          | 0.0043                 | 0.1586 | 0.0365      | 0.0215           | 0.1007    |
+| 0.4302        | 3.0   | 762  | 0.4624          | 0.0043                 | 0.1579 | 0.0388      | 0.0179           | 0.1012    |
+| 0.3421        | 4.0   | 1016 | 0.4778          | 0.0043                 | 0.1599 | 0.0403      | 0.0162           | 0.1034    |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.8.0+cu126
+- Datasets 3.6.0
+- Tokenizers 0.21.4

model.safetensors

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