metadata
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: 0.59375
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: 1.2364
- Accuracy: 0.5938
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0702 | 1.0 | 10 | 2.0666 | 0.1437 |
| 2.0583 | 2.0 | 20 | 2.0476 | 0.2125 |
| 2.0291 | 3.0 | 30 | 2.0018 | 0.3 |
| 1.9639 | 4.0 | 40 | 1.9175 | 0.3563 |
| 1.8582 | 5.0 | 50 | 1.7997 | 0.4375 |
| 1.7385 | 6.0 | 60 | 1.6756 | 0.4625 |
| 1.5984 | 7.0 | 70 | 1.5469 | 0.4625 |
| 1.4739 | 8.0 | 80 | 1.4684 | 0.5188 |
| 1.3737 | 9.0 | 90 | 1.4090 | 0.5125 |
| 1.2719 | 10.0 | 100 | 1.3740 | 0.525 |
| 1.2072 | 11.0 | 110 | 1.3527 | 0.55 |
| 1.1158 | 12.0 | 120 | 1.3118 | 0.5188 |
| 1.0487 | 13.0 | 130 | 1.2349 | 0.6 |
| 0.9873 | 14.0 | 140 | 1.2931 | 0.525 |
| 0.8928 | 15.0 | 150 | 1.2731 | 0.55 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1