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: results
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: 0.48125
results
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: 1.5240
- Accuracy: 0.4813
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 80 | 2.0769 | 0.1562 |
| No log | 2.0 | 160 | 2.0542 | 0.2125 |
| No log | 3.0 | 240 | 1.9931 | 0.3125 |
| No log | 4.0 | 320 | 1.8756 | 0.2938 |
| No log | 5.0 | 400 | 1.6917 | 0.3875 |
| No log | 6.0 | 480 | 1.5471 | 0.4188 |
| 1.7305 | 7.0 | 560 | 1.4615 | 0.4562 |
| 1.7305 | 8.0 | 640 | 1.4356 | 0.4688 |
| 1.7305 | 9.0 | 720 | 1.3676 | 0.4875 |
| 1.7305 | 10.0 | 800 | 1.4125 | 0.5062 |
| 1.7305 | 11.0 | 880 | 1.5065 | 0.4688 |
| 1.7305 | 12.0 | 960 | 1.5047 | 0.4938 |
| 0.3363 | 13.0 | 1040 | 1.5180 | 0.4875 |
| 0.3363 | 14.0 | 1120 | 1.5228 | 0.4813 |
| 0.3363 | 15.0 | 1200 | 1.5240 | 0.4813 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0