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speaker-segmentation-fine-tuned-callhome-jpn
evie-8/speaker-segmentation-fine-tuned-callhome-jpn
speaker-segmentation-fine-tuned-callhome-jpn is a machine learning model from evie-8. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- pyannet
- Access
- Public
- Created
- Jul 8, 2024
- Updated
- Jul 8, 2024
- SHA
- 7840f258
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
speaker-segmentation-fine-tuned-callhome-jpn
This model is a fine-tuned version of pyannote/segmentation-3.0 on the diarizers-community/callhome jpn dataset. It achieves the following results on the evaluation set:
- Loss: 0.7545
- Der: 0.2264
- False Alarm: 0.0488
- Missed Detection: 0.1331
- Confusion: 0.0445
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|
| 0.562 | 1.0 | 328 | 0.7605 | 0.2346 | 0.0492 | 0.1357 | 0.0497 |
| 0.5564 | 2.0 | 656 | 0.7540 | 0.2294 | 0.0512 | 0.1328 | 0.0454 |
| 0.5273 | 3.0 | 984 | 0.7724 | 0.2321 | 0.0438 | 0.1419 | 0.0464 |
| 0.5037 | 4.0 | 1312 | 0.7599 | 0.2276 | 0.0475 | 0.1349 | 0.0452 |
| 0.5041 | 5.0 | 1640 | 0.7545 | 0.2264 | 0.0488 | 0.1331 | 0.0445 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- pyannet
- License
- mit
- Created
- Jul 8, 2024
- Updated
- Jul 8, 2024