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speaker-segmentation-fine-tuned-callhome-spa-10e
mrm8488/speaker-segmentation-fine-tuned-callhome-spa-10e
speaker-segmentation-fine-tuned-callhome-spa-10e is a machine learning model from mrm8488. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- pyannet
- Access
- Public
- Created
- Apr 24, 2024
- Updated
- Apr 24, 2024
- SHA
- 116d3730
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. -->
mrm8488/speaker-segmentation-fine-tuned-callhome-spa-10e
This model is a fine-tuned version of openai/whisper-small on the diarizers-community/callhome dataset. It achieves the following results on the evaluation set:
- Loss: 0.5210
- Der: 0.1743
- False Alarm: 0.0765
- Missed Detection: 0.0670
- Confusion: 0.0308
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|
| 0.6545 | 1.0 | 382 | 0.5338 | 0.1797 | 0.0637 | 0.0805 | 0.0355 |
| 0.6125 | 2.0 | 764 | 0.5097 | 0.1738 | 0.0720 | 0.0692 | 0.0326 |
| 0.6118 | 3.0 | 1146 | 0.5102 | 0.1709 | 0.0588 | 0.0799 | 0.0322 |
| 0.6064 | 4.0 | 1528 | 0.5138 | 0.1707 | 0.0657 | 0.0754 | 0.0296 |
| 0.572 | 5.0 | 1910 | 0.5126 | 0.1727 | 0.0709 | 0.0714 | 0.0304 |
| 0.5671 | 6.0 | 2292 | 0.5161 | 0.1731 | 0.0771 | 0.0654 | 0.0306 |
| 0.533 | 7.0 | 2674 | 0.5143 | 0.1732 | 0.0712 | 0.0715 | 0.0305 |
| 0.551 | 8.0 | 3056 | 0.5207 | 0.1739 | 0.0716 | 0.0717 | 0.0307 |
| 0.5543 | 9.0 | 3438 | 0.5199 | 0.1738 | 0.0756 | 0.0676 | 0.0306 |
| 0.5234 | 10.0 | 3820 | 0.5210 | 0.1743 | 0.0765 | 0.0670 | 0.0308 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- pyannet
- License
- apache-2.0
- Languages
- spa
- Created
- Apr 24, 2024
- Updated
- Apr 24, 2024