File size: 4,736 Bytes
3c5f9fa f4e952d 3c5f9fa f4e952d 3c5f9fa f4e952d 3c5f9fa |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ViT_bean_leaves_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ViT_bean_leaves_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0320
- Accuracy: 1.0
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0335 | 0.0769 | 10 | 0.9775 | 0.6165 |
| 0.8744 | 0.1538 | 20 | 0.8419 | 0.8647 |
| 0.7576 | 0.2308 | 30 | 0.6803 | 0.9248 |
| 0.5918 | 0.3077 | 40 | 0.5376 | 0.9624 |
| 0.4833 | 0.3846 | 50 | 0.4257 | 0.9699 |
| 0.3873 | 0.4615 | 60 | 0.3395 | 0.9624 |
| 0.3508 | 0.5385 | 70 | 0.2656 | 0.9774 |
| 0.3008 | 0.6154 | 80 | 0.2369 | 0.9549 |
| 0.2282 | 0.6923 | 90 | 0.1895 | 0.9925 |
| 0.204 | 0.7692 | 100 | 0.1596 | 0.9699 |
| 0.213 | 0.8462 | 110 | 0.1350 | 0.9925 |
| 0.1618 | 0.9231 | 120 | 0.1679 | 0.9624 |
| 0.1657 | 1.0 | 130 | 0.1061 | 0.9925 |
| 0.0997 | 1.0769 | 140 | 0.1020 | 0.9925 |
| 0.1185 | 1.1538 | 150 | 0.0892 | 0.9925 |
| 0.1329 | 1.2308 | 160 | 0.0903 | 1.0 |
| 0.0671 | 1.3077 | 170 | 0.0767 | 1.0 |
| 0.0634 | 1.3846 | 180 | 0.0696 | 0.9925 |
| 0.0618 | 1.4615 | 190 | 0.0631 | 1.0 |
| 0.0896 | 1.5385 | 200 | 0.0687 | 0.9925 |
| 0.0519 | 1.6154 | 210 | 0.0641 | 0.9925 |
| 0.052 | 1.6923 | 220 | 0.0580 | 0.9925 |
| 0.049 | 1.7692 | 230 | 0.0707 | 0.9925 |
| 0.1221 | 1.8462 | 240 | 0.0723 | 0.9925 |
| 0.0798 | 1.9231 | 250 | 0.0645 | 0.9850 |
| 0.043 | 2.0 | 260 | 0.0590 | 0.9925 |
| 0.0461 | 2.0769 | 270 | 0.0549 | 0.9850 |
| 0.0391 | 2.1538 | 280 | 0.0626 | 0.9925 |
| 0.0368 | 2.2308 | 290 | 0.0612 | 0.9925 |
| 0.0357 | 2.3077 | 300 | 0.0510 | 0.9925 |
| 0.035 | 2.3846 | 310 | 0.0448 | 1.0 |
| 0.0339 | 2.4615 | 320 | 0.0437 | 1.0 |
| 0.0352 | 2.5385 | 330 | 0.0454 | 0.9925 |
| 0.0315 | 2.6154 | 340 | 0.0457 | 0.9925 |
| 0.1151 | 2.6923 | 350 | 0.0390 | 1.0 |
| 0.0324 | 2.7692 | 360 | 0.0386 | 1.0 |
| 0.0298 | 2.8462 | 370 | 0.0370 | 1.0 |
| 0.0316 | 2.9231 | 380 | 0.0363 | 1.0 |
| 0.0295 | 3.0 | 390 | 0.0363 | 1.0 |
| 0.0284 | 3.0769 | 400 | 0.0363 | 1.0 |
| 0.0278 | 3.1538 | 410 | 0.0357 | 1.0 |
| 0.0296 | 3.2308 | 420 | 0.0352 | 1.0 |
| 0.0299 | 3.3077 | 430 | 0.0348 | 1.0 |
| 0.0277 | 3.3846 | 440 | 0.0351 | 1.0 |
| 0.0301 | 3.4615 | 450 | 0.0331 | 1.0 |
| 0.0281 | 3.5385 | 460 | 0.0328 | 1.0 |
| 0.0279 | 3.6154 | 470 | 0.0325 | 1.0 |
| 0.0283 | 3.6923 | 480 | 0.0324 | 1.0 |
| 0.0278 | 3.7692 | 490 | 0.0323 | 1.0 |
| 0.0286 | 3.8462 | 500 | 0.0322 | 1.0 |
| 0.0267 | 3.9231 | 510 | 0.0321 | 1.0 |
| 0.0276 | 4.0 | 520 | 0.0320 | 1.0 |
### Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
|