End of training

README.md

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+---
+library_name: transformers
+language:
+- id
+license: mit
+base_model: pyannote/speaker-diarization-3.1
+tags:
+- speaker-diarization
+- speaker-segmentation
+- modality:audio
+- modality:text
+- format:parquet
+- generated_from_trainer
+datasets:
+- speaker-segmentation
+model-index:
+- name: speaker-segmentation-fine-tuned-id
+  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-id
+
+This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the speaker-segmentation dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3798
+- Model Preparation Time: 0.0039
+- Der: 0.1196
+- False Alarm: 0.0617
+- Missed Detection: 0.0232
+- Confusion: 0.0346
+
+## 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: 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
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.6461        | 1.0   | 47   | 0.4005          | 0.0039                 | 0.1328 | 0.0651      | 0.0212           | 0.0465    |
+| 0.5243        | 2.0   | 94   | 0.3903          | 0.0039                 | 0.1253 | 0.0615      | 0.0236           | 0.0402    |
+| 0.4921        | 3.0   | 141  | 0.3782          | 0.0039                 | 0.1203 | 0.0622      | 0.0226           | 0.0355    |
+| 0.4775        | 4.0   | 188  | 0.3828          | 0.0039                 | 0.1202 | 0.0615      | 0.0236           | 0.0350    |
+| 0.4764        | 5.0   | 235  | 0.3798          | 0.0039                 | 0.1196 | 0.0617      | 0.0232           | 0.0346    |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.0
+- Tokenizers 0.21.0

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runs/Mar17_02-23-12_3f8793441e71/events.out.tfevents.1742178212.3f8793441e71.285.0

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