File size: 4,824 Bytes
aac469b |
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: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_adamax_00001_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: 0.7777777777777778
---
<!-- 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_5x_beit_base_adamax_00001_fold2
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: 1.0731
- Accuracy: 0.7778
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.133 | 1.0 | 27 | 1.1782 | 0.4444 |
| 0.7374 | 2.0 | 54 | 0.9657 | 0.6889 |
| 0.4404 | 3.0 | 81 | 0.7664 | 0.7556 |
| 0.2921 | 4.0 | 108 | 0.7034 | 0.7778 |
| 0.1574 | 5.0 | 135 | 0.7044 | 0.7778 |
| 0.0983 | 6.0 | 162 | 0.6550 | 0.8222 |
| 0.0636 | 7.0 | 189 | 0.6911 | 0.7778 |
| 0.0455 | 8.0 | 216 | 0.6445 | 0.8 |
| 0.0369 | 9.0 | 243 | 0.7441 | 0.8 |
| 0.0208 | 10.0 | 270 | 0.7266 | 0.8222 |
| 0.0164 | 11.0 | 297 | 0.7445 | 0.8 |
| 0.0128 | 12.0 | 324 | 0.7928 | 0.7556 |
| 0.0152 | 13.0 | 351 | 0.8051 | 0.8 |
| 0.0093 | 14.0 | 378 | 0.8366 | 0.8 |
| 0.005 | 15.0 | 405 | 0.8967 | 0.7778 |
| 0.0081 | 16.0 | 432 | 0.8765 | 0.7556 |
| 0.0143 | 17.0 | 459 | 0.8233 | 0.8 |
| 0.0086 | 18.0 | 486 | 0.8818 | 0.7778 |
| 0.0082 | 19.0 | 513 | 0.9209 | 0.7778 |
| 0.0106 | 20.0 | 540 | 0.9710 | 0.7778 |
| 0.0048 | 21.0 | 567 | 0.8635 | 0.8 |
| 0.0078 | 22.0 | 594 | 1.0340 | 0.7778 |
| 0.0037 | 23.0 | 621 | 1.0458 | 0.7778 |
| 0.0038 | 24.0 | 648 | 1.0554 | 0.7778 |
| 0.0027 | 25.0 | 675 | 0.9290 | 0.8 |
| 0.0037 | 26.0 | 702 | 0.9379 | 0.7778 |
| 0.006 | 27.0 | 729 | 0.9412 | 0.8 |
| 0.001 | 28.0 | 756 | 0.9493 | 0.8 |
| 0.0018 | 29.0 | 783 | 1.0041 | 0.8 |
| 0.0014 | 30.0 | 810 | 1.0318 | 0.8 |
| 0.0008 | 31.0 | 837 | 1.0197 | 0.8 |
| 0.0016 | 32.0 | 864 | 1.0685 | 0.7556 |
| 0.005 | 33.0 | 891 | 1.0574 | 0.7556 |
| 0.0013 | 34.0 | 918 | 1.0948 | 0.7556 |
| 0.0027 | 35.0 | 945 | 1.0699 | 0.7556 |
| 0.0008 | 36.0 | 972 | 1.0485 | 0.8 |
| 0.0014 | 37.0 | 999 | 1.0539 | 0.7778 |
| 0.0009 | 38.0 | 1026 | 1.0508 | 0.7778 |
| 0.0013 | 39.0 | 1053 | 1.0236 | 0.7778 |
| 0.0008 | 40.0 | 1080 | 1.0556 | 0.8 |
| 0.0014 | 41.0 | 1107 | 1.0682 | 0.8 |
| 0.0011 | 42.0 | 1134 | 1.0760 | 0.8 |
| 0.0041 | 43.0 | 1161 | 1.0831 | 0.8 |
| 0.0007 | 44.0 | 1188 | 1.0675 | 0.7778 |
| 0.0039 | 45.0 | 1215 | 1.0667 | 0.7778 |
| 0.0013 | 46.0 | 1242 | 1.0695 | 0.7778 |
| 0.0014 | 47.0 | 1269 | 1.0717 | 0.7778 |
| 0.0015 | 48.0 | 1296 | 1.0731 | 0.7778 |
| 0.002 | 49.0 | 1323 | 1.0731 | 0.7778 |
| 0.0013 | 50.0 | 1350 | 1.0731 | 0.7778 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|