File size: 4,812 Bytes
fb4a98d |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 |
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_001_fold2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.17777777777777778
---
<!-- 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. -->
# hushem_1x_deit_tiny_sgd_001_fold2
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4913
- Accuracy: 0.1778
## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.6461 | 0.2222 |
| 1.647 | 2.0 | 12 | 1.5827 | 0.2 |
| 1.647 | 3.0 | 18 | 1.5400 | 0.2 |
| 1.5111 | 4.0 | 24 | 1.5101 | 0.2 |
| 1.4472 | 5.0 | 30 | 1.4855 | 0.1778 |
| 1.4472 | 6.0 | 36 | 1.4711 | 0.1778 |
| 1.3765 | 7.0 | 42 | 1.4618 | 0.2 |
| 1.3765 | 8.0 | 48 | 1.4555 | 0.2 |
| 1.3363 | 9.0 | 54 | 1.4523 | 0.2222 |
| 1.3131 | 10.0 | 60 | 1.4505 | 0.2 |
| 1.3131 | 11.0 | 66 | 1.4495 | 0.2 |
| 1.2743 | 12.0 | 72 | 1.4504 | 0.2 |
| 1.2743 | 13.0 | 78 | 1.4505 | 0.2 |
| 1.2923 | 14.0 | 84 | 1.4516 | 0.2 |
| 1.2475 | 15.0 | 90 | 1.4529 | 0.2 |
| 1.2475 | 16.0 | 96 | 1.4558 | 0.2 |
| 1.2052 | 17.0 | 102 | 1.4591 | 0.1778 |
| 1.2052 | 18.0 | 108 | 1.4603 | 0.1778 |
| 1.2375 | 19.0 | 114 | 1.4628 | 0.1778 |
| 1.1665 | 20.0 | 120 | 1.4654 | 0.1778 |
| 1.1665 | 21.0 | 126 | 1.4668 | 0.1778 |
| 1.1508 | 22.0 | 132 | 1.4681 | 0.1778 |
| 1.1508 | 23.0 | 138 | 1.4710 | 0.1778 |
| 1.1615 | 24.0 | 144 | 1.4735 | 0.1778 |
| 1.1372 | 25.0 | 150 | 1.4742 | 0.1778 |
| 1.1372 | 26.0 | 156 | 1.4775 | 0.1778 |
| 1.1389 | 27.0 | 162 | 1.4787 | 0.1778 |
| 1.1389 | 28.0 | 168 | 1.4813 | 0.1778 |
| 1.1191 | 29.0 | 174 | 1.4821 | 0.1778 |
| 1.106 | 30.0 | 180 | 1.4844 | 0.1778 |
| 1.106 | 31.0 | 186 | 1.4853 | 0.1778 |
| 1.1156 | 32.0 | 192 | 1.4867 | 0.1778 |
| 1.1156 | 33.0 | 198 | 1.4872 | 0.1778 |
| 1.127 | 34.0 | 204 | 1.4879 | 0.1778 |
| 1.1055 | 35.0 | 210 | 1.4887 | 0.1778 |
| 1.1055 | 36.0 | 216 | 1.4895 | 0.1778 |
| 1.089 | 37.0 | 222 | 1.4902 | 0.1778 |
| 1.089 | 38.0 | 228 | 1.4907 | 0.1778 |
| 1.0605 | 39.0 | 234 | 1.4911 | 0.1778 |
| 1.0925 | 40.0 | 240 | 1.4913 | 0.1778 |
| 1.0925 | 41.0 | 246 | 1.4913 | 0.1778 |
| 1.1025 | 42.0 | 252 | 1.4913 | 0.1778 |
| 1.1025 | 43.0 | 258 | 1.4913 | 0.1778 |
| 1.1085 | 44.0 | 264 | 1.4913 | 0.1778 |
| 1.0909 | 45.0 | 270 | 1.4913 | 0.1778 |
| 1.0909 | 46.0 | 276 | 1.4913 | 0.1778 |
| 1.0889 | 47.0 | 282 | 1.4913 | 0.1778 |
| 1.0889 | 48.0 | 288 | 1.4913 | 0.1778 |
| 1.0611 | 49.0 | 294 | 1.4913 | 0.1778 |
| 1.1045 | 50.0 | 300 | 1.4913 | 0.1778 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|