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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: pyannote/segmentation-3.0
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+ tags:
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+ - speaker-diarization
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+ - speaker-segmentation
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+ - generated_from_trainer
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+ datasets:
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+ - diarizers-community/callhome
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+ model-index:
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+ - name: speaker-segmentation-fine-tuned-callhome-eng
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # speaker-segmentation-fine-tuned-callhome-eng
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+
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+ This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome eng dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4602
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+ - Der: 0.1828
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+ - False Alarm: 0.0584
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+ - Missed Detection: 0.0717
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+ - Confusion: 0.0528
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 5.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
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+ | 0.4123 | 1.0 | 362 | 0.4801 | 0.1930 | 0.0627 | 0.0741 | 0.0563 |
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+ | 0.3906 | 2.0 | 724 | 0.4558 | 0.1836 | 0.0589 | 0.0727 | 0.0519 |
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+ | 0.3753 | 3.0 | 1086 | 0.4643 | 0.1830 | 0.0557 | 0.0746 | 0.0527 |
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+ | 0.3632 | 4.0 | 1448 | 0.4566 | 0.1821 | 0.0564 | 0.0728 | 0.0529 |
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+ | 0.3475 | 5.0 | 1810 | 0.4602 | 0.1828 | 0.0584 | 0.0717 | 0.0528 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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