speaker-segmentation-fine-tuned-shreyasdesaisuperU
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5045
- Model Preparation Time: 0.004
- Der: 0.7087
- False Alarm: 0.1651
- Missed Detection: 0.4934
- Confusion: 0.0502
Model description
More information needed
Intended uses & limitations
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|---|
| 0.5024 | 1.0 | 1320 | 0.5060 | 0.004 | 0.7136 | 0.2101 | 0.4428 | 0.0607 |
| 0.4691 | 2.0 | 2640 | 0.4981 | 0.004 | 0.7086 | 0.2132 | 0.4415 | 0.0539 |
| 0.4771 | 3.0 | 3960 | 0.5074 | 0.004 | 0.7227 | 0.1439 | 0.5320 | 0.0468 |
| 0.4464 | 4.0 | 5280 | 0.5025 | 0.004 | 0.7097 | 0.1532 | 0.5078 | 0.0487 |
| 0.4618 | 5.0 | 6600 | 0.5045 | 0.004 | 0.7087 | 0.1651 | 0.4934 | 0.0502 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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