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README.md ADDED
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+ ---
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+ language:
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+ - spa
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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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: mrm8488/speaker-segmentation-fine-tuned-callhome-spa-10e
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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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+ # mrm8488/speaker-segmentation-fine-tuned-callhome-spa-10e
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the diarizers-community/callhome dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5210
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+ - Der: 0.1743
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+ - False Alarm: 0.0765
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+ - Missed Detection: 0.0670
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+ - Confusion: 0.0308
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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: 10
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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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+ | 0.6545 | 1.0 | 382 | 0.5338 | 0.1797 | 0.0637 | 0.0805 | 0.0355 |
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+ | 0.6125 | 2.0 | 764 | 0.5097 | 0.1738 | 0.0720 | 0.0692 | 0.0326 |
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+ | 0.6118 | 3.0 | 1146 | 0.5102 | 0.1709 | 0.0588 | 0.0799 | 0.0322 |
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+ | 0.6064 | 4.0 | 1528 | 0.5138 | 0.1707 | 0.0657 | 0.0754 | 0.0296 |
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+ | 0.572 | 5.0 | 1910 | 0.5126 | 0.1727 | 0.0709 | 0.0714 | 0.0304 |
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+ | 0.5671 | 6.0 | 2292 | 0.5161 | 0.1731 | 0.0771 | 0.0654 | 0.0306 |
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+ | 0.533 | 7.0 | 2674 | 0.5143 | 0.1732 | 0.0712 | 0.0715 | 0.0305 |
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+ | 0.551 | 8.0 | 3056 | 0.5207 | 0.1739 | 0.0716 | 0.0717 | 0.0307 |
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+ | 0.5543 | 9.0 | 3438 | 0.5199 | 0.1738 | 0.0756 | 0.0676 | 0.0306 |
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+ | 0.5234 | 10.0 | 3820 | 0.5210 | 0.1743 | 0.0765 | 0.0670 | 0.0308 |
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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 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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