metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans
results: []
vit-base-beans
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset. It achieves the following results on the evaluation set:
- Loss: 0.0079
- 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.2859 | 1.0 | 130 | 0.9624 | 0.2189 |
| 0.1316 | 2.0 | 260 | 0.9699 | 0.1334 |
| 0.1438 | 3.0 | 390 | 0.9699 | 0.0981 |
| 0.0833 | 4.0 | 520 | 0.9925 | 0.0656 |
| 0.1107 | 5.0 | 650 | 0.9774 | 0.0817 |
| 0.098 | 11.0 | 715 | 0.9925 | 0.0570 |
| 0.0935 | 12.0 | 780 | 1.0 | 0.0418 |
| 0.0907 | 13.0 | 845 | 0.9699 | 0.1093 |
| 0.0947 | 14.0 | 910 | 1.0 | 0.0347 |
| 0.1259 | 15.0 | 975 | 0.9850 | 0.0710 |
| 0.0325 | 16.0 | 1040 | 0.9774 | 0.0587 |
| 0.1397 | 17.0 | 1105 | 0.9925 | 0.0495 |
| 0.0456 | 18.0 | 1170 | 0.9774 | 0.0519 |
| 0.0439 | 19.0 | 1235 | 1.0 | 0.0216 |
| 0.0484 | 20.0 | 1300 | 0.9925 | 0.0316 |
| 0.0276 | 21.0 | 1365 | 1.0 | 0.0192 |
| 0.0348 | 22.0 | 1430 | 1.0 | 0.0177 |
| 0.0326 | 23.0 | 1495 | 1.0 | 0.0175 |
| 0.1014 | 24.0 | 1560 | 0.9925 | 0.0235 |
| 0.0395 | 25.0 | 1625 | 0.9850 | 0.0451 |
| 0.0265 | 26.0 | 1690 | 0.9925 | 0.0297 |
| 0.0569 | 27.0 | 1755 | 0.9925 | 0.0263 |
| 0.0666 | 28.0 | 1820 | 0.9850 | 0.0245 |
| 0.0285 | 29.0 | 1885 | 0.9774 | 0.0418 |
| 0.0892 | 30.0 | 1950 | 0.9925 | 0.0204 |
| 0.0371 | 31.0 | 2015 | 0.9850 | 0.0339 |
| 0.0105 | 32.0 | 2080 | 1.0 | 0.0143 |
| 0.0563 | 33.0 | 2145 | 1.0 | 0.0140 |
| 0.0573 | 34.0 | 2210 | 1.0 | 0.0102 |
| 0.0409 | 35.0 | 2275 | 1.0 | 0.0096 |
| 0.0523 | 36.0 | 2340 | 0.9925 | 0.0149 |
| 0.0131 | 37.0 | 2405 | 0.9925 | 0.0197 |
| 0.0329 | 38.0 | 2470 | 1.0 | 0.0109 |
| 0.0577 | 39.0 | 2535 | 1.0 | 0.0096 |
| 0.0085 | 40.0 | 2600 | 0.9925 | 0.0147 |
| 0.0618 | 41.0 | 2665 | 1.0 | 0.0094 |
| 0.0847 | 42.0 | 2730 | 0.9925 | 0.0197 |
| 0.0291 | 43.0 | 2795 | 1.0 | 0.0089 |
| 0.0568 | 44.0 | 2860 | 1.0 | 0.0087 |
| 0.0077 | 45.0 | 2925 | 1.0 | 0.0104 |
| 0.008 | 46.0 | 2990 | 1.0 | 0.0138 |
| 0.0272 | 47.0 | 3055 | 1.0 | 0.0081 |
| 0.008 | 48.0 | 3120 | 1.0 | 0.0084 |
| 0.0112 | 49.0 | 3185 | 1.0 | 0.0082 |
| 0.013 | 50.0 | 3250 | 1.0 | 0.0079 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1