portrait_cosu_exp3
This model is a fine-tuned version of NekoFi/content-manage-exp2 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2524
- Accuracy: 0.9149
- Precision: 0.9190
- Recall: 0.9149
- F1: 0.9153
- Confusion Matrix: [[19, 1], [3, 24]]
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Confusion Matrix |
---|---|---|---|---|---|---|---|---|
No log | 0.9231 | 6 | 0.2921 | 0.8511 | 0.8527 | 0.8511 | 0.8515 | [[17, 3], [4, 23]] |
0.5415 | 2.0 | 13 | 0.2564 | 0.9362 | 0.9426 | 0.9362 | 0.9353 | [[17, 3], [0, 27]] |
0.5415 | 2.9231 | 19 | 0.3605 | 0.8723 | 0.8864 | 0.8723 | 0.8730 | [[19, 1], [5, 22]] |
0.378 | 3.6923 | 24 | 0.2524 | 0.9149 | 0.9190 | 0.9149 | 0.9153 | [[19, 1], [3, 24]] |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Evaluation results
- Accuracy on imagefolderself-reported0.915
- Precision on imagefolderself-reported0.919
- Recall on imagefolderself-reported0.915
- F1 on imagefolderself-reported0.915