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profesor_Swin3D_N_VIOPERU
DanJoshua/profesor_Swin3D_N_VIOPERU
profesor_Swin3D_N_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_N_VIOPERU
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5378
- Accuracy: 0.7946
- F1: 0.7946
- Precision: 0.7947
- Recall: 0.7946
- Roc Auc: 0.8677
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 |
|---|---|---|---|---|---|---|---|---|
| 1.3382 | 2.0161 | 37 | 0.6576 | 0.7321 | 0.7279 | 0.7476 | 0.7321 | 0.7781 |
| 1.2814 | 5.0071 | 74 | 0.6126 | 0.7679 | 0.7678 | 0.7682 | 0.7679 | 0.8508 |
| 1.152 | 7.0232 | 111 | 0.5517 | 0.8036 | 0.8035 | 0.8040 | 0.8036 | 0.8546 |
| 0.8907 | 10.0143 | 148 | 0.5129 | 0.7679 | 0.7678 | 0.7682 | 0.7679 | 0.8673 |
| 0.7726 | 13.0054 | 185 | 0.4512 | 0.7857 | 0.7854 | 0.7872 | 0.7857 | 0.8827 |
| 0.6067 | 15.0214 | 222 | 0.4228 | 0.8036 | 0.8030 | 0.8071 | 0.8036 | 0.8929 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
- Library
- transformers
- Created
- Nov 2, 2024
- Updated
- Nov 3, 2024