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resnet-152-fv-finetuned-memess
This model is a fine-tuned version of microsoft/resnet-152 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6281
- Accuracy: 0.7674
- Precision: 0.7651
- Recall: 0.7674
- F1: 0.7647
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: 0.00012
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.5902 | 0.99 | 20 | 1.5519 | 0.4938 | 0.3491 | 0.4938 | 0.3529 |
| 1.4694 | 1.99 | 40 | 1.3730 | 0.4892 | 0.4095 | 0.4892 | 0.3222 |
| 1.3129 | 2.99 | 60 | 1.2052 | 0.5301 | 0.3504 | 0.5301 | 0.4005 |
| 1.1831 | 3.99 | 80 | 1.1142 | 0.5587 | 0.4077 | 0.5587 | 0.4444 |
| 1.0581 | 4.99 | 100 | 0.9930 | 0.6012 | 0.5680 | 0.6012 | 0.5108 |
| 0.9464 | 5.99 | 120 | 0.9263 | 0.6507 | 0.6200 | 0.6507 | 0.6029 |
| 0.8581 | 6.99 | 140 | 0.8400 | 0.6917 | 0.6645 | 0.6917 | 0.6638 |
| 0.7739 | 7.99 | 160 | 0.7829 | 0.7087 | 0.6918 | 0.7087 | 0.6845 |
| 0.6762 | 8.99 | 180 | 0.7512 | 0.7318 | 0.7206 | 0.7318 | 0.7189 |
| 0.6162 | 9.99 | 200 | 0.7409 | 0.7264 | 0.7244 | 0.7264 | 0.7241 |
| 0.5546 | 10.99 | 220 | 0.6936 | 0.7465 | 0.7429 | 0.7465 | 0.7395 |
| 0.4633 | 11.99 | 240 | 0.6779 | 0.7473 | 0.7393 | 0.7473 | 0.7412 |
| 0.4373 | 12.99 | 260 | 0.6736 | 0.7573 | 0.7492 | 0.7573 | 0.7523 |
| 0.4074 | 13.99 | 280 | 0.6534 | 0.7566 | 0.7516 | 0.7566 | 0.7528 |
| 0.39 | 14.99 | 300 | 0.6521 | 0.7651 | 0.7603 | 0.7651 | 0.7608 |
| 0.3766 | 15.99 | 320 | 0.6499 | 0.7682 | 0.7607 | 0.7682 | 0.7630 |
| 0.3507 | 16.99 | 340 | 0.6497 | 0.7697 | 0.7686 | 0.7697 | 0.7686 |
| 0.3589 | 17.99 | 360 | 0.6519 | 0.7535 | 0.7485 | 0.7535 | 0.7502 |
| 0.3261 | 18.99 | 380 | 0.6449 | 0.7589 | 0.7597 | 0.7589 | 0.7585 |
| 0.3234 | 19.99 | 400 | 0.6281 | 0.7674 | 0.7651 | 0.7674 | 0.7647 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1.dev0
- Tokenizers 0.13.1
