End of training
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README.md
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---
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language:
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- jpn
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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: speaker-segmentation-fine-tuned-callhome-jpn
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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-callhome-jpn
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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: 0.7479
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- Der: 0.2241
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- False Alarm: 0.0478
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- Missed Detection: 0.1332
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- Confusion: 0.0431
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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
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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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| 0.5757 | 1.0 | 328 | 0.7460 | 0.2299 | 0.0502 | 0.1343 | 0.0454 |
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| 0.5219 | 2.0 | 656 | 0.7482 | 0.2251 | 0.0486 | 0.1340 | 0.0425 |
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| 0.5067 | 3.0 | 984 | 0.7539 | 0.2259 | 0.0454 | 0.1369 | 0.0435 |
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| 0.4923 | 4.0 | 1312 | 0.7453 | 0.2246 | 0.0490 | 0.1320 | 0.0436 |
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| 0.5157 | 5.0 | 1640 | 0.7479 | 0.2241 | 0.0478 | 0.1332 | 0.0431 |
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### Framework versions
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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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runs/Apr27_04-52-46_40a69929f82a/events.out.tfevents.1714193585.40a69929f82a.157.0
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size
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size 21280
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