File size: 4,900 Bytes
3b97c15 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-finetuned-context-classifier
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: 0.8187702265372169
---
<!-- 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. -->
# vit-base-patch16-224-finetuned-context-classifier
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7157
- Accuracy: 0.8188
## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3586 | 2.0 | 10 | 1.2322 | 0.3916 |
| 1.0841 | 4.0 | 20 | 0.8444 | 0.6958 |
| 0.7282 | 6.0 | 30 | 0.5498 | 0.7767 |
| 0.4768 | 8.0 | 40 | 0.4273 | 0.8155 |
| 0.3332 | 10.0 | 50 | 0.4059 | 0.8220 |
| 0.242 | 12.0 | 60 | 0.4272 | 0.8252 |
| 0.1737 | 14.0 | 70 | 0.4372 | 0.8188 |
| 0.1266 | 16.0 | 80 | 0.4495 | 0.8123 |
| 0.1089 | 18.0 | 90 | 0.4877 | 0.8091 |
| 0.0837 | 20.0 | 100 | 0.5318 | 0.8058 |
| 0.0687 | 22.0 | 110 | 0.5300 | 0.7961 |
| 0.0667 | 24.0 | 120 | 0.6253 | 0.7994 |
| 0.0581 | 26.0 | 130 | 0.5495 | 0.8220 |
| 0.0574 | 28.0 | 140 | 0.5646 | 0.8188 |
| 0.0564 | 30.0 | 150 | 0.5990 | 0.8252 |
| 0.0492 | 32.0 | 160 | 0.6436 | 0.8155 |
| 0.0406 | 34.0 | 170 | 0.6225 | 0.8091 |
| 0.0411 | 36.0 | 180 | 0.6168 | 0.8123 |
| 0.0381 | 38.0 | 190 | 0.6731 | 0.8123 |
| 0.0358 | 40.0 | 200 | 0.6198 | 0.7961 |
| 0.0354 | 42.0 | 210 | 0.6216 | 0.8091 |
| 0.0358 | 44.0 | 220 | 0.6933 | 0.8091 |
| 0.037 | 46.0 | 230 | 0.6488 | 0.8188 |
| 0.0344 | 48.0 | 240 | 0.6546 | 0.8220 |
| 0.0335 | 50.0 | 250 | 0.6399 | 0.7994 |
| 0.0297 | 52.0 | 260 | 0.6553 | 0.8123 |
| 0.0318 | 54.0 | 270 | 0.6996 | 0.7896 |
| 0.0254 | 56.0 | 280 | 0.6809 | 0.7961 |
| 0.0322 | 58.0 | 290 | 0.7048 | 0.7896 |
| 0.024 | 60.0 | 300 | 0.6869 | 0.8123 |
| 0.0255 | 62.0 | 310 | 0.7099 | 0.8058 |
| 0.0266 | 64.0 | 320 | 0.6894 | 0.8091 |
| 0.0243 | 66.0 | 330 | 0.7604 | 0.8091 |
| 0.0232 | 68.0 | 340 | 0.6983 | 0.8123 |
| 0.019 | 70.0 | 350 | 0.6834 | 0.8091 |
| 0.0235 | 72.0 | 360 | 0.7102 | 0.8091 |
| 0.0262 | 74.0 | 370 | 0.6902 | 0.8155 |
| 0.0206 | 76.0 | 380 | 0.6662 | 0.8091 |
| 0.0238 | 78.0 | 390 | 0.7109 | 0.8220 |
| 0.0202 | 80.0 | 400 | 0.7061 | 0.8058 |
| 0.0204 | 82.0 | 410 | 0.7291 | 0.8155 |
| 0.0231 | 84.0 | 420 | 0.7103 | 0.8091 |
| 0.0217 | 86.0 | 430 | 0.7050 | 0.8123 |
| 0.021 | 88.0 | 440 | 0.7037 | 0.8155 |
| 0.0207 | 90.0 | 450 | 0.6996 | 0.8058 |
| 0.0163 | 92.0 | 460 | 0.7137 | 0.8091 |
| 0.0181 | 94.0 | 470 | 0.7153 | 0.8155 |
| 0.0225 | 96.0 | 480 | 0.7105 | 0.8123 |
| 0.0185 | 98.0 | 490 | 0.7140 | 0.8155 |
| 0.0219 | 100.0 | 500 | 0.7157 | 0.8188 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.4
- Tokenizers 0.14.1
|