convnextv2-base-1k-224-for-pre_evaluation
This model is a fine-tuned version of facebook/convnextv2-base-1k-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3599
- Accuracy: 0.4190
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6 | 1.0 | 16 | 1.5316 | 0.2961 |
| 1.5084 | 2.0 | 32 | 1.5061 | 0.2849 |
| 1.5134 | 3.0 | 48 | 1.4968 | 0.3240 |
| 1.4663 | 4.0 | 64 | 1.4607 | 0.3352 |
| 1.4046 | 5.0 | 80 | 1.4509 | 0.3268 |
| 1.4085 | 6.0 | 96 | 1.4423 | 0.3883 |
| 1.3443 | 7.0 | 112 | 1.4005 | 0.4022 |
| 1.3025 | 8.0 | 128 | 1.3599 | 0.4190 |
| 1.2627 | 9.0 | 144 | 1.3638 | 0.3911 |
| 1.2099 | 10.0 | 160 | 1.4058 | 0.3492 |
| 1.2086 | 11.0 | 176 | 1.4431 | 0.3408 |
| 1.1393 | 12.0 | 192 | 1.4143 | 0.3492 |
| 1.1039 | 13.0 | 208 | 1.4305 | 0.3883 |
| 1.0551 | 14.0 | 224 | 1.5203 | 0.3520 |
| 1.0368 | 15.0 | 240 | 1.5117 | 0.3324 |
| 0.9753 | 16.0 | 256 | 1.4545 | 0.3771 |
| 0.938 | 17.0 | 272 | 1.5396 | 0.3352 |
| 0.899 | 18.0 | 288 | 1.5770 | 0.3408 |
| 0.8629 | 19.0 | 304 | 1.7106 | 0.3128 |
| 0.8674 | 20.0 | 320 | 1.5864 | 0.3352 |
| 0.7789 | 21.0 | 336 | 1.6129 | 0.3408 |
| 0.7426 | 22.0 | 352 | 1.6353 | 0.3603 |
| 0.7677 | 23.0 | 368 | 1.6793 | 0.3464 |
| 0.7172 | 24.0 | 384 | 1.6759 | 0.3575 |
| 0.6809 | 25.0 | 400 | 1.7013 | 0.3659 |
| 0.6619 | 26.0 | 416 | 1.7108 | 0.3631 |
| 0.6656 | 27.0 | 432 | 1.7327 | 0.3715 |
| 0.6258 | 28.0 | 448 | 1.7378 | 0.3547 |
| 0.6173 | 29.0 | 464 | 1.7461 | 0.3603 |
| 0.6214 | 30.0 | 480 | 1.7475 | 0.3520 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3