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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: 0.4607
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+ - Der: 0.1815
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+ - False Alarm: 0.0596
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+ - Missed Detection: 0.0708
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+ - Confusion: 0.0511
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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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+ | 0.426 | 1.0 | 362 | 0.4667 | 0.1875 | 0.0549 | 0.0784 | 0.0542 |
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+ | 0.392 | 2.0 | 724 | 0.4678 | 0.1852 | 0.0594 | 0.0721 | 0.0536 |
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+ | 0.3722 | 3.0 | 1086 | 0.4561 | 0.1801 | 0.0578 | 0.0714 | 0.0509 |
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+ | 0.351 | 4.0 | 1448 | 0.4565 | 0.1810 | 0.0597 | 0.0699 | 0.0515 |
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+ | 0.3493 | 5.0 | 1810 | 0.4607 | 0.1815 | 0.0596 | 0.0708 | 0.0511 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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