metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: LC_Classification_mymodel
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: 0.8126984126984127
LC_Classification_mymodel
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4954
- Accuracy: 0.8127
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: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5039 | 1.0 | 20 | 1.4275 | 0.2540 |
| 1.1888 | 2.0 | 40 | 1.1616 | 0.4730 |
| 1.0682 | 3.0 | 60 | 1.0345 | 0.5302 |
| 0.8865 | 4.0 | 80 | 0.9234 | 0.5683 |
| 0.7938 | 5.0 | 100 | 0.8973 | 0.5492 |
| 0.7519 | 6.0 | 120 | 0.8358 | 0.6127 |
| 0.6776 | 7.0 | 140 | 0.8197 | 0.6222 |
| 0.5899 | 8.0 | 160 | 0.7399 | 0.6635 |
| 0.5905 | 9.0 | 180 | 0.7407 | 0.6381 |
| 0.5343 | 10.0 | 200 | 0.7049 | 0.7143 |
| 0.4882 | 11.0 | 220 | 0.6190 | 0.7333 |
| 0.4188 | 12.0 | 240 | 0.6137 | 0.7524 |
| 0.4429 | 13.0 | 260 | 0.5947 | 0.7556 |
| 0.4362 | 14.0 | 280 | 0.6187 | 0.7175 |
| 0.3318 | 15.0 | 300 | 0.5669 | 0.7683 |
| 0.3945 | 16.0 | 320 | 0.5443 | 0.7937 |
| 0.3985 | 17.0 | 340 | 0.5436 | 0.8095 |
| 0.2732 | 18.0 | 360 | 0.5000 | 0.8222 |
| 0.3049 | 19.0 | 380 | 0.5211 | 0.8 |
| 0.2911 | 20.0 | 400 | 0.5371 | 0.7714 |
| 0.2853 | 21.0 | 420 | 0.4954 | 0.8127 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.1