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profesor_Swin3D_B_VIOPERU
DanJoshua/profesor_Swin3D_B_VIOPERU
profesor_Swin3D_B_VIOPERU is a machine learning model from DanJoshua. 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.
should probably proofread and complete it, then remove this comment. --
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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. -->
profesor_Swin3D_B_VIOPERU
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4563
- Accuracy: 0.8571
- F1: 0.8571
- Precision: 0.8571
- Recall: 0.8571
- Roc Auc: 0.9037
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 84
- training_steps: 560
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 1.3718 | 2.0161 | 37 | 0.6728 | 0.6607 | 0.6166 | 0.7979 | 0.6607 | 0.7666 |
| 1.307 | 5.0071 | 74 | 0.6388 | 0.8393 | 0.8367 | 0.8619 | 0.8393 | 0.8367 |
| 1.2244 | 7.0232 | 111 | 0.5896 | 0.8036 | 0.8020 | 0.8136 | 0.8036 | 0.8508 |
| 1.0091 | 10.0143 | 148 | 0.5448 | 0.8214 | 0.8205 | 0.8281 | 0.8214 | 0.8648 |
| 0.8839 | 13.0054 | 185 | 0.4877 | 0.8393 | 0.8380 | 0.8505 | 0.8393 | 0.8763 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
- Library
- transformers
- Created
- Nov 3, 2024
- Updated
- Nov 3, 2024