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cvt-13-384-in22k-FV-finetuned-memes
This model is a fine-tuned version of microsoft/cvt-13-384-22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5595
- Accuracy: 0.8346
- Precision: 0.8327
- Recall: 0.8346
- F1: 0.8322
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 |
|---|---|---|---|---|---|---|---|
| 1.4066 | 0.99 | 20 | 1.2430 | 0.5124 | 0.5141 | 0.5124 | 0.4371 |
| 1.0813 | 1.99 | 40 | 0.8244 | 0.6893 | 0.6834 | 0.6893 | 0.6616 |
| 0.8392 | 2.99 | 60 | 0.6334 | 0.7612 | 0.7670 | 0.7612 | 0.7570 |
| 0.7065 | 3.99 | 80 | 0.5819 | 0.7767 | 0.7799 | 0.7767 | 0.7672 |
| 0.5751 | 4.99 | 100 | 0.5365 | 0.8176 | 0.8216 | 0.8176 | 0.8130 |
| 0.4896 | 5.99 | 120 | 0.4943 | 0.8308 | 0.8257 | 0.8308 | 0.8265 |
| 0.4487 | 6.99 | 140 | 0.5399 | 0.8107 | 0.8069 | 0.8107 | 0.8054 |
| 0.4349 | 7.99 | 160 | 0.4892 | 0.8300 | 0.8285 | 0.8300 | 0.8273 |
| 0.43 | 8.99 | 180 | 0.4984 | 0.8454 | 0.8465 | 0.8454 | 0.8426 |
| 0.4372 | 9.99 | 200 | 0.5573 | 0.8192 | 0.8221 | 0.8192 | 0.8157 |
| 0.3994 | 10.99 | 220 | 0.5158 | 0.8300 | 0.8284 | 0.8300 | 0.8281 |
| 0.3883 | 11.99 | 240 | 0.5495 | 0.8354 | 0.8317 | 0.8354 | 0.8314 |
| 0.406 | 12.99 | 260 | 0.5298 | 0.8284 | 0.8285 | 0.8284 | 0.8246 |
| 0.3355 | 13.99 | 280 | 0.5401 | 0.8393 | 0.8346 | 0.8393 | 0.8357 |
| 0.395 | 14.99 | 300 | 0.5915 | 0.8308 | 0.8278 | 0.8308 | 0.8261 |
| 0.3612 | 15.99 | 320 | 0.5852 | 0.8408 | 0.8378 | 0.8408 | 0.8368 |
| 0.3765 | 16.99 | 340 | 0.5509 | 0.8385 | 0.8351 | 0.8385 | 0.8356 |
| 0.3688 | 17.99 | 360 | 0.5668 | 0.8416 | 0.8398 | 0.8416 | 0.8387 |
| 0.3503 | 18.99 | 380 | 0.5626 | 0.8393 | 0.8371 | 0.8393 | 0.8365 |
| 0.3611 | 19.99 | 400 | 0.5595 | 0.8346 | 0.8327 | 0.8346 | 0.8322 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1.dev0
- Tokenizers 0.13.1
