resnet152-FV-finetuned-memes
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: 0.6772
- Accuracy: 0.7558
- Precision: 0.7557
- Recall: 0.7558
- F1: 0.7546
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 |
|---|---|---|---|---|---|---|---|
| 1.5739 | 0.99 | 20 | 1.5427 | 0.4521 | 0.3131 | 0.4521 | 0.2880 |
| 1.4353 | 1.99 | 40 | 1.3786 | 0.4490 | 0.3850 | 0.4490 | 0.2791 |
| 1.3026 | 2.99 | 60 | 1.2734 | 0.4799 | 0.3073 | 0.4799 | 0.3393 |
| 1.1579 | 3.99 | 80 | 1.1378 | 0.5278 | 0.4300 | 0.5278 | 0.4143 |
| 1.0276 | 4.99 | 100 | 1.0231 | 0.5734 | 0.4497 | 0.5734 | 0.4865 |
| 0.8826 | 5.99 | 120 | 0.9228 | 0.6252 | 0.5983 | 0.6252 | 0.5637 |
| 0.766 | 6.99 | 140 | 0.8441 | 0.6662 | 0.6474 | 0.6662 | 0.6320 |
| 0.6732 | 7.99 | 160 | 0.8009 | 0.6901 | 0.6759 | 0.6901 | 0.6704 |
| 0.5653 | 8.99 | 180 | 0.7535 | 0.7218 | 0.7141 | 0.7218 | 0.7129 |
| 0.4957 | 9.99 | 200 | 0.7317 | 0.7257 | 0.7248 | 0.7257 | 0.7200 |
| 0.4534 | 10.99 | 220 | 0.6808 | 0.7434 | 0.7405 | 0.7434 | 0.7390 |
| 0.3792 | 11.99 | 240 | 0.6949 | 0.7450 | 0.7454 | 0.7450 | 0.7399 |
| 0.3489 | 12.99 | 260 | 0.6746 | 0.7496 | 0.7511 | 0.7496 | 0.7474 |
| 0.3113 | 13.99 | 280 | 0.6637 | 0.7573 | 0.7638 | 0.7573 | 0.7579 |
| 0.2947 | 14.99 | 300 | 0.6451 | 0.7589 | 0.7667 | 0.7589 | 0.7610 |
| 0.2776 | 15.99 | 320 | 0.6754 | 0.7543 | 0.7565 | 0.7543 | 0.7525 |
| 0.2611 | 16.99 | 340 | 0.6808 | 0.7550 | 0.7607 | 0.7550 | 0.7529 |
| 0.2428 | 17.99 | 360 | 0.7005 | 0.7457 | 0.7497 | 0.7457 | 0.7404 |
| 0.2346 | 18.99 | 380 | 0.6597 | 0.7573 | 0.7642 | 0.7573 | 0.7590 |
| 0.2367 | 19.99 | 400 | 0.6772 | 0.7558 | 0.7557 | 0.7558 | 0.7546 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1.dev0
- Tokenizers 0.13.1