File size: 4,815 Bytes
30c6692 |
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_rms_00001_fold3
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: 0.7674418604651163
---
<!-- 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_rms_00001_fold3
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: 0.6755
- Accuracy: 0.7674
## 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: 1e-05
- 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 | 1.2450 | 0.3953 |
| 1.3266 | 2.0 | 12 | 1.0282 | 0.4884 |
| 1.3266 | 3.0 | 18 | 0.8766 | 0.6512 |
| 0.6113 | 4.0 | 24 | 0.8143 | 0.6279 |
| 0.301 | 5.0 | 30 | 0.9703 | 0.6047 |
| 0.301 | 6.0 | 36 | 0.7894 | 0.7209 |
| 0.1194 | 7.0 | 42 | 0.8712 | 0.6512 |
| 0.1194 | 8.0 | 48 | 0.7416 | 0.6744 |
| 0.0478 | 9.0 | 54 | 0.7289 | 0.6744 |
| 0.0192 | 10.0 | 60 | 0.6181 | 0.7209 |
| 0.0192 | 11.0 | 66 | 0.7194 | 0.6977 |
| 0.007 | 12.0 | 72 | 0.6519 | 0.6744 |
| 0.007 | 13.0 | 78 | 0.6428 | 0.7209 |
| 0.0038 | 14.0 | 84 | 0.6323 | 0.6977 |
| 0.0027 | 15.0 | 90 | 0.6303 | 0.7209 |
| 0.0027 | 16.0 | 96 | 0.6496 | 0.7209 |
| 0.0021 | 17.0 | 102 | 0.6367 | 0.7209 |
| 0.0021 | 18.0 | 108 | 0.6386 | 0.7209 |
| 0.0018 | 19.0 | 114 | 0.6562 | 0.7442 |
| 0.0015 | 20.0 | 120 | 0.6541 | 0.7442 |
| 0.0015 | 21.0 | 126 | 0.6493 | 0.7442 |
| 0.0014 | 22.0 | 132 | 0.6669 | 0.7442 |
| 0.0014 | 23.0 | 138 | 0.6543 | 0.7674 |
| 0.0012 | 24.0 | 144 | 0.6581 | 0.7442 |
| 0.0011 | 25.0 | 150 | 0.6534 | 0.7442 |
| 0.0011 | 26.0 | 156 | 0.6644 | 0.7442 |
| 0.001 | 27.0 | 162 | 0.6622 | 0.7674 |
| 0.001 | 28.0 | 168 | 0.6583 | 0.7442 |
| 0.001 | 29.0 | 174 | 0.6594 | 0.7674 |
| 0.0009 | 30.0 | 180 | 0.6672 | 0.7674 |
| 0.0009 | 31.0 | 186 | 0.6681 | 0.7674 |
| 0.0008 | 32.0 | 192 | 0.6656 | 0.7674 |
| 0.0008 | 33.0 | 198 | 0.6699 | 0.7674 |
| 0.0008 | 34.0 | 204 | 0.6718 | 0.7674 |
| 0.0008 | 35.0 | 210 | 0.6718 | 0.7674 |
| 0.0008 | 36.0 | 216 | 0.6735 | 0.7674 |
| 0.0008 | 37.0 | 222 | 0.6740 | 0.7674 |
| 0.0008 | 38.0 | 228 | 0.6754 | 0.7674 |
| 0.0007 | 39.0 | 234 | 0.6750 | 0.7674 |
| 0.0007 | 40.0 | 240 | 0.6751 | 0.7674 |
| 0.0007 | 41.0 | 246 | 0.6753 | 0.7674 |
| 0.0007 | 42.0 | 252 | 0.6755 | 0.7674 |
| 0.0007 | 43.0 | 258 | 0.6755 | 0.7674 |
| 0.0007 | 44.0 | 264 | 0.6755 | 0.7674 |
| 0.0007 | 45.0 | 270 | 0.6755 | 0.7674 |
| 0.0007 | 46.0 | 276 | 0.6755 | 0.7674 |
| 0.0007 | 47.0 | 282 | 0.6755 | 0.7674 |
| 0.0007 | 48.0 | 288 | 0.6755 | 0.7674 |
| 0.0007 | 49.0 | 294 | 0.6755 | 0.7674 |
| 0.0007 | 50.0 | 300 | 0.6755 | 0.7674 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|