metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.5625
image_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.2386
- Accuracy: 0.5625
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0874 | 1.0 | 10 | 2.0621 | 0.2313 |
| 2.036 | 2.0 | 20 | 2.0392 | 0.2375 |
| 1.9297 | 3.0 | 30 | 1.9592 | 0.3 |
| 1.7723 | 4.0 | 40 | 1.7877 | 0.3937 |
| 1.6184 | 5.0 | 50 | 1.6475 | 0.45 |
| 1.5407 | 6.0 | 60 | 1.5514 | 0.4875 |
| 1.4197 | 7.0 | 70 | 1.4967 | 0.4938 |
| 1.3092 | 8.0 | 80 | 1.4332 | 0.4813 |
| 1.1251 | 9.0 | 90 | 1.4457 | 0.4688 |
| 1.2081 | 10.0 | 100 | 1.3603 | 0.4938 |
| 0.9803 | 11.0 | 110 | 1.3501 | 0.5188 |
| 1.0105 | 12.0 | 120 | 1.3212 | 0.55 |
| 0.9264 | 13.0 | 130 | 1.2895 | 0.575 |
| 0.9229 | 14.0 | 140 | 1.2882 | 0.5188 |
| 0.9397 | 15.0 | 150 | 1.4027 | 0.475 |
| 0.8322 | 16.0 | 160 | 1.2824 | 0.5312 |
| 0.8185 | 17.0 | 170 | 1.3025 | 0.5 |
| 0.7592 | 18.0 | 180 | 1.3629 | 0.475 |
| 0.7416 | 19.0 | 190 | 1.3221 | 0.5437 |
| 0.6323 | 20.0 | 200 | 1.2714 | 0.5563 |
| 0.6453 | 21.0 | 210 | 1.3015 | 0.4938 |
| 0.6049 | 22.0 | 220 | 1.3065 | 0.5375 |
| 0.5919 | 23.0 | 230 | 1.2579 | 0.5375 |
| 0.5354 | 24.0 | 240 | 1.2428 | 0.55 |
| 0.6379 | 25.0 | 250 | 1.2884 | 0.5375 |
| 0.5681 | 26.0 | 260 | 1.2201 | 0.5938 |
| 0.4275 | 27.0 | 270 | 1.3199 | 0.4875 |
| 0.4791 | 28.0 | 280 | 1.3027 | 0.5312 |
| 0.4693 | 29.0 | 290 | 1.3737 | 0.4813 |
| 0.5528 | 30.0 | 300 | 1.3342 | 0.4688 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1