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profesor_Swin3D_N_RWF2000
DanJoshua/profesor_Swin3D_N_RWF2000
profesor_Swin3D_N_RWF2000 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_RWF2000
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7124
- Accuracy: 0.89
- F1: 0.8899
- Precision: 0.8914
- Recall: 0.89
- Roc Auc: 0.9556
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: 1e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- 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: 480
- training_steps: 4800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 0.3362 | 2.0333 | 480 | 0.2416 | 0.8975 | 0.8975 | 0.8980 | 0.8975 | 0.9708 |
| 0.19 | 5.0333 | 960 | 0.3867 | 0.9 | 0.8998 | 0.9026 | 0.9 | 0.9715 |
| 0.118 | 8.0333 | 1440 | 0.4950 | 0.905 | 0.9047 | 0.9100 | 0.905 | 0.9664 |
| 0.0623 | 11.0333 | 1920 | 0.4876 | 0.9025 | 0.9024 | 0.9048 | 0.9025 | 0.9741 |
| 0.11 | 14.0333 | 2400 | 0.6291 | 0.905 | 0.9049 | 0.9060 | 0.905 | 0.9619 |
| 0.0617 | 17.0333 | 2880 | 0.6637 | 0.8975 | 0.8974 | 0.8983 | 0.8975 | 0.9671 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1
- Library
- transformers
- Created
- Oct 31, 2024
- Updated
- Oct 31, 2024