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: 0.5375
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: 1.3659
- Accuracy: 0.5375
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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 32 | 1.9290 | 0.3063 |
| No log | 2.0 | 64 | 1.6622 | 0.3563 |
| No log | 3.0 | 96 | 1.5753 | 0.3937 |
| No log | 4.0 | 128 | 1.5099 | 0.475 |
| No log | 5.0 | 160 | 1.4614 | 0.4313 |
| No log | 6.0 | 192 | 1.4104 | 0.5 |
| No log | 7.0 | 224 | 1.3962 | 0.4562 |
| No log | 8.0 | 256 | 1.3535 | 0.5437 |
| No log | 9.0 | 288 | 1.3483 | 0.5062 |
| No log | 10.0 | 320 | 1.3994 | 0.45 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3