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: trainer_output
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: None
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.5126527801687037
trainer_output
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: 1.4766
- Accuracy: 0.5127
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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- 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: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9670 | 22 | 2.0708 | 0.1449 |
| No log | 1.9670 | 44 | 2.0653 | 0.1663 |
| 2.0961 | 2.9670 | 66 | 2.0564 | 0.1931 |
| 2.0961 | 3.9670 | 88 | 2.0423 | 0.2350 |
| 2.0586 | 4.9670 | 110 | 2.0171 | 0.2823 |
| 2.0586 | 5.9670 | 132 | 1.9638 | 0.3305 |
| 1.9128 | 6.9670 | 154 | 1.8130 | 0.3968 |
| 1.9128 | 7.9670 | 176 | 1.6647 | 0.4278 |
| 1.9128 | 8.9670 | 198 | 1.5676 | 0.4844 |
| 1.6466 | 9.9670 | 220 | 1.4766 | 0.5127 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0