metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: CIDAUTv2
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: 0.75
CIDAUTv2
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5012
- Accuracy: 0.75
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 4 | 0.7104 | 0.5139 |
| No log | 2.0 | 8 | 0.6436 | 0.6065 |
| 0.685 | 3.0 | 12 | 0.6004 | 0.6944 |
| 0.685 | 4.0 | 16 | 0.5978 | 0.6759 |
| 0.5422 | 5.0 | 20 | 0.5582 | 0.7222 |
| 0.5422 | 6.0 | 24 | 0.5222 | 0.7361 |
| 0.5422 | 7.0 | 28 | 0.5060 | 0.7222 |
| 0.4521 | 8.0 | 32 | 0.4957 | 0.7269 |
| 0.4521 | 9.0 | 36 | 0.4781 | 0.75 |
| 0.3741 | 10.0 | 40 | 0.5012 | 0.75 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0