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: 0.50625
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: 1.5890
- Accuracy: 0.5062
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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 10 | 2.0332 | 0.25 |
| No log | 2.0 | 20 | 1.9720 | 0.3125 |
| No log | 3.0 | 30 | 1.8937 | 0.3688 |
| No log | 4.0 | 40 | 1.8265 | 0.375 |
| No log | 5.0 | 50 | 1.7561 | 0.3937 |
| No log | 6.0 | 60 | 1.7083 | 0.45 |
| No log | 7.0 | 70 | 1.6719 | 0.4375 |
| No log | 8.0 | 80 | 1.6415 | 0.4688 |
| No log | 9.0 | 90 | 1.6237 | 0.4813 |
| No log | 10.0 | 100 | 1.6041 | 0.4938 |
| No log | 11.0 | 110 | 1.5890 | 0.5062 |
| No log | 12.0 | 120 | 1.5774 | 0.5 |
| No log | 13.0 | 130 | 1.5700 | 0.5 |
| No log | 14.0 | 140 | 1.5659 | 0.5062 |
| No log | 15.0 | 150 | 1.5643 | 0.5062 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1