End of training
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README.md
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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/ami
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model-index:
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- name: speaker-segmentation-fine-tuned-ami
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results: []
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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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# speaker-segmentation-fine-tuned-ami
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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/ami ihm dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3660
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- Der: 0.1396
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- False Alarm: 0.0503
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- Missed Detection: 0.0578
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- Confusion: 0.0314
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
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| 0.4133 | 1.0 | 1427 | 0.3629 | 0.1388 | 0.0424 | 0.0646 | 0.0318 |
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| 0.3907 | 2.0 | 2854 | 0.3638 | 0.1400 | 0.0492 | 0.0583 | 0.0324 |
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| 0.3651 | 3.0 | 4281 | 0.3631 | 0.1403 | 0.0506 | 0.0581 | 0.0316 |
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| 0.3692 | 4.0 | 5708 | 0.3643 | 0.1394 | 0.0489 | 0.0591 | 0.0314 |
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| 0.3484 | 5.0 | 7135 | 0.3660 | 0.1396 | 0.0503 | 0.0578 | 0.0314 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.0+cu121
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- Datasets 2.17.0
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- Tokenizers 0.19.1
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model.safetensors
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runs/May02_11-10-59_aitest2/events.out.tfevents.1714637700.aitest2.2324498.0
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