image_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1494
- Accuracy: 0.6062
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| 1.8347 |
1.0 |
10 |
1.9052 |
0.3688 |
| 1.838 |
2.0 |
20 |
1.7999 |
0.375 |
| 1.7193 |
3.0 |
30 |
1.6869 |
0.35 |
| 1.5873 |
4.0 |
40 |
1.5855 |
0.4437 |
| 1.4919 |
5.0 |
50 |
1.4977 |
0.475 |
| 1.4049 |
6.0 |
60 |
1.4425 |
0.4875 |
| 1.3025 |
7.0 |
70 |
1.4254 |
0.45 |
| 1.238 |
8.0 |
80 |
1.3994 |
0.475 |
| 1.1704 |
9.0 |
90 |
1.3109 |
0.5312 |
| 1.1009 |
10.0 |
100 |
1.3309 |
0.525 |
| 1.0309 |
11.0 |
110 |
1.2941 |
0.5687 |
| 0.9705 |
12.0 |
120 |
1.2750 |
0.5188 |
| 0.9315 |
13.0 |
130 |
1.2402 |
0.55 |
| 0.8894 |
14.0 |
140 |
1.2425 |
0.5375 |
| 0.8374 |
15.0 |
150 |
1.2273 |
0.525 |
| 0.8 |
16.0 |
160 |
1.2454 |
0.5125 |
| 0.7597 |
17.0 |
170 |
1.2445 |
0.5125 |
| 0.7143 |
18.0 |
180 |
1.1750 |
0.5687 |
| 0.6832 |
19.0 |
190 |
1.2456 |
0.525 |
| 0.6573 |
20.0 |
200 |
1.2004 |
0.5938 |
| 0.639 |
21.0 |
210 |
1.1924 |
0.5563 |
| 0.635 |
22.0 |
220 |
1.1257 |
0.6 |
| 0.5982 |
23.0 |
230 |
1.1845 |
0.575 |
| 0.5675 |
24.0 |
240 |
1.2291 |
0.5625 |
| 0.5634 |
25.0 |
250 |
1.1837 |
0.5687 |
| 0.535 |
26.0 |
260 |
1.2384 |
0.5813 |
| 0.5233 |
27.0 |
270 |
1.1911 |
0.5875 |
| 0.529 |
28.0 |
280 |
1.2083 |
0.5875 |
| 0.5141 |
29.0 |
290 |
1.1813 |
0.5875 |
| 0.5166 |
30.0 |
300 |
1.1578 |
0.5938 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
