deit-base-patch16-224-finetuned-ind-14-imbalanced-pan-10847-train
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4660
- Accuracy: 0.8703
- Recall: 0.8703
- F1: 0.8412
- Precision: 0.8253
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | Precision |
---|---|---|---|---|---|---|---|
0.7292 | 0.99 | 43 | 0.6759 | 0.7925 | 0.7925 | 0.7582 | 0.7420 |
0.5224 | 2.0 | 87 | 0.5146 | 0.8501 | 0.8501 | 0.8228 | 0.8057 |
0.5103 | 2.97 | 129 | 0.4916 | 0.8674 | 0.8674 | 0.8391 | 0.8244 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
facebook/deit-base-patch16-224Evaluation results
- Accuracy on imagefolderself-reported0.870
- Recall on imagefolderself-reported0.870
- F1 on imagefolderself-reported0.841
- Precision on imagefolderself-reported0.825