|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/beit-base-patch16-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: beit-base-patch16-224-hasta-75-fold4 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 1.0 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# beit-base-patch16-224-hasta-75-fold4 |
|
|
|
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0812 |
|
- 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: 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: 100 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 1 | 2.3241 | 0.0833 | |
|
| No log | 2.0 | 2 | 1.8900 | 0.0833 | |
|
| No log | 3.0 | 3 | 1.1748 | 0.3333 | |
|
| No log | 4.0 | 4 | 0.5751 | 0.9167 | |
|
| No log | 5.0 | 5 | 0.4224 | 0.9167 | |
|
| No log | 6.0 | 6 | 0.3931 | 0.9167 | |
|
| No log | 7.0 | 7 | 0.3635 | 0.9167 | |
|
| No log | 8.0 | 8 | 0.5637 | 0.8333 | |
|
| No log | 9.0 | 9 | 0.4256 | 0.9167 | |
|
| 0.4996 | 10.0 | 10 | 0.2830 | 0.9167 | |
|
| 0.4996 | 11.0 | 11 | 0.2743 | 0.9167 | |
|
| 0.4996 | 12.0 | 12 | 0.4505 | 0.9167 | |
|
| 0.4996 | 13.0 | 13 | 0.3552 | 0.9167 | |
|
| 0.4996 | 14.0 | 14 | 0.2453 | 0.9167 | |
|
| 0.4996 | 15.0 | 15 | 0.2528 | 0.9167 | |
|
| 0.4996 | 16.0 | 16 | 0.2926 | 0.9167 | |
|
| 0.4996 | 17.0 | 17 | 0.3253 | 0.8333 | |
|
| 0.4996 | 18.0 | 18 | 0.3367 | 0.8333 | |
|
| 0.4996 | 19.0 | 19 | 0.3681 | 0.8333 | |
|
| 0.1796 | 20.0 | 20 | 0.2677 | 0.9167 | |
|
| 0.1796 | 21.0 | 21 | 0.2704 | 0.9167 | |
|
| 0.1796 | 22.0 | 22 | 0.3116 | 0.9167 | |
|
| 0.1796 | 23.0 | 23 | 0.3650 | 0.9167 | |
|
| 0.1796 | 24.0 | 24 | 0.2170 | 0.9167 | |
|
| 0.1796 | 25.0 | 25 | 0.2114 | 0.9167 | |
|
| 0.1796 | 26.0 | 26 | 0.1976 | 0.9167 | |
|
| 0.1796 | 27.0 | 27 | 0.1619 | 0.9167 | |
|
| 0.1796 | 28.0 | 28 | 0.1646 | 0.9167 | |
|
| 0.1796 | 29.0 | 29 | 0.1432 | 0.9167 | |
|
| 0.1179 | 30.0 | 30 | 0.0812 | 1.0 | |
|
| 0.1179 | 31.0 | 31 | 0.1163 | 1.0 | |
|
| 0.1179 | 32.0 | 32 | 0.0898 | 1.0 | |
|
| 0.1179 | 33.0 | 33 | 0.1190 | 0.9167 | |
|
| 0.1179 | 34.0 | 34 | 0.1464 | 0.9167 | |
|
| 0.1179 | 35.0 | 35 | 0.1136 | 1.0 | |
|
| 0.1179 | 36.0 | 36 | 0.2270 | 0.9167 | |
|
| 0.1179 | 37.0 | 37 | 0.2265 | 0.9167 | |
|
| 0.1179 | 38.0 | 38 | 0.0995 | 1.0 | |
|
| 0.1179 | 39.0 | 39 | 0.0853 | 1.0 | |
|
| 0.1084 | 40.0 | 40 | 0.0858 | 1.0 | |
|
| 0.1084 | 41.0 | 41 | 0.0970 | 1.0 | |
|
| 0.1084 | 42.0 | 42 | 0.0949 | 1.0 | |
|
| 0.1084 | 43.0 | 43 | 0.0709 | 1.0 | |
|
| 0.1084 | 44.0 | 44 | 0.0807 | 0.9167 | |
|
| 0.1084 | 45.0 | 45 | 0.1052 | 0.9167 | |
|
| 0.1084 | 46.0 | 46 | 0.0629 | 1.0 | |
|
| 0.1084 | 47.0 | 47 | 0.0272 | 1.0 | |
|
| 0.1084 | 48.0 | 48 | 0.0775 | 1.0 | |
|
| 0.1084 | 49.0 | 49 | 0.1113 | 1.0 | |
|
| 0.0591 | 50.0 | 50 | 0.1189 | 1.0 | |
|
| 0.0591 | 51.0 | 51 | 0.0526 | 1.0 | |
|
| 0.0591 | 52.0 | 52 | 0.0262 | 1.0 | |
|
| 0.0591 | 53.0 | 53 | 0.1035 | 0.9167 | |
|
| 0.0591 | 54.0 | 54 | 0.1508 | 0.9167 | |
|
| 0.0591 | 55.0 | 55 | 0.1280 | 0.9167 | |
|
| 0.0591 | 56.0 | 56 | 0.0652 | 0.9167 | |
|
| 0.0591 | 57.0 | 57 | 0.0357 | 1.0 | |
|
| 0.0591 | 58.0 | 58 | 0.0407 | 1.0 | |
|
| 0.0591 | 59.0 | 59 | 0.0430 | 1.0 | |
|
| 0.0637 | 60.0 | 60 | 0.0468 | 1.0 | |
|
| 0.0637 | 61.0 | 61 | 0.0997 | 0.9167 | |
|
| 0.0637 | 62.0 | 62 | 0.2200 | 0.9167 | |
|
| 0.0637 | 63.0 | 63 | 0.2979 | 0.9167 | |
|
| 0.0637 | 64.0 | 64 | 0.3167 | 0.9167 | |
|
| 0.0637 | 65.0 | 65 | 0.2611 | 0.9167 | |
|
| 0.0637 | 66.0 | 66 | 0.1697 | 0.9167 | |
|
| 0.0637 | 67.0 | 67 | 0.0669 | 0.9167 | |
|
| 0.0637 | 68.0 | 68 | 0.0313 | 1.0 | |
|
| 0.0637 | 69.0 | 69 | 0.0255 | 1.0 | |
|
| 0.0446 | 70.0 | 70 | 0.0243 | 1.0 | |
|
| 0.0446 | 71.0 | 71 | 0.0188 | 1.0 | |
|
| 0.0446 | 72.0 | 72 | 0.0210 | 1.0 | |
|
| 0.0446 | 73.0 | 73 | 0.0261 | 1.0 | |
|
| 0.0446 | 74.0 | 74 | 0.0378 | 1.0 | |
|
| 0.0446 | 75.0 | 75 | 0.0492 | 1.0 | |
|
| 0.0446 | 76.0 | 76 | 0.0679 | 0.9167 | |
|
| 0.0446 | 77.0 | 77 | 0.0958 | 0.9167 | |
|
| 0.0446 | 78.0 | 78 | 0.0803 | 0.9167 | |
|
| 0.0446 | 79.0 | 79 | 0.0455 | 1.0 | |
|
| 0.0489 | 80.0 | 80 | 0.0194 | 1.0 | |
|
| 0.0489 | 81.0 | 81 | 0.0141 | 1.0 | |
|
| 0.0489 | 82.0 | 82 | 0.0109 | 1.0 | |
|
| 0.0489 | 83.0 | 83 | 0.0104 | 1.0 | |
|
| 0.0489 | 84.0 | 84 | 0.0108 | 1.0 | |
|
| 0.0489 | 85.0 | 85 | 0.0121 | 1.0 | |
|
| 0.0489 | 86.0 | 86 | 0.0118 | 1.0 | |
|
| 0.0489 | 87.0 | 87 | 0.0109 | 1.0 | |
|
| 0.0489 | 88.0 | 88 | 0.0107 | 1.0 | |
|
| 0.0489 | 89.0 | 89 | 0.0107 | 1.0 | |
|
| 0.0322 | 90.0 | 90 | 0.0107 | 1.0 | |
|
| 0.0322 | 91.0 | 91 | 0.0107 | 1.0 | |
|
| 0.0322 | 92.0 | 92 | 0.0106 | 1.0 | |
|
| 0.0322 | 93.0 | 93 | 0.0105 | 1.0 | |
|
| 0.0322 | 94.0 | 94 | 0.0105 | 1.0 | |
|
| 0.0322 | 95.0 | 95 | 0.0105 | 1.0 | |
|
| 0.0322 | 96.0 | 96 | 0.0106 | 1.0 | |
|
| 0.0322 | 97.0 | 97 | 0.0106 | 1.0 | |
|
| 0.0322 | 98.0 | 98 | 0.0106 | 1.0 | |
|
| 0.0322 | 99.0 | 99 | 0.0108 | 1.0 | |
|
| 0.0405 | 100.0 | 100 | 0.0109 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
