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profesor_MViT_N_RWF2000
DanJoshua/profesor_MViT_N_RWF2000
profesor_MViT_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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At a glance
- Library
- transformers
- Access
- Public
- Created
- Oct 30, 2024
- Updated
- Oct 30, 2024
- SHA
- cdfc18a2
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_MViT_N_RWF2000
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2366
- Accuracy: 0.92
- F1: 0.9200
- Precision: 0.9205
- Recall: 0.92
- Roc Auc: 0.9722
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: 20
- eval_batch_size: 20
- 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: 240
- training_steps: 2400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 0.5576 | 2.0333 | 240 | 0.4177 | 0.89 | 0.8900 | 0.8902 | 0.89 | 0.9554 |
| 0.2715 | 5.0333 | 480 | 0.2499 | 0.9225 | 0.9225 | 0.9234 | 0.9225 | 0.9768 |
| 0.1905 | 8.0333 | 720 | 0.2218 | 0.925 | 0.9250 | 0.9261 | 0.925 | 0.9799 |
| 0.1934 | 11.0333 | 960 | 0.2321 | 0.9125 | 0.9125 | 0.9125 | 0.9125 | 0.9791 |
| 0.1371 | 14.0333 | 1200 | 0.2527 | 0.9225 | 0.9224 | 0.9249 | 0.9225 | 0.9817 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.0.1+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1
- Library
- transformers
- Created
- Oct 30, 2024
- Updated
- Oct 30, 2024