metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: >-
vit_epochs5_batch32_lr5e-05_size224_tiles1_seed1_classic_image_classification_t
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: Dogs_vs_Cats
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9954666666666667
vit_epochs5_batch32_lr5e-05_size224_tiles1_seed1_classic_image_classification_t
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the Dogs_vs_Cats dataset. It achieves the following results on the evaluation set:
- Loss: 0.0171
- Accuracy: 0.9955
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.006 | 1.0 | 469 | 0.0248 | 0.9925 |
| 0.0019 | 2.0 | 938 | 0.0275 | 0.9931 |
| 0.0012 | 3.0 | 1407 | 0.0207 | 0.9952 |
| 0.0008 | 4.0 | 1876 | 0.0171 | 0.9955 |
| 0.0007 | 5.0 | 2345 | 0.0181 | 0.9955 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1