|
---
|
|
license: apache-2.0
|
|
base_model: google/vit-base-patch16-224
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- imagenet-1k
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: vit-base-patch16-224-finetuned-eurosat
|
|
results:
|
|
- task:
|
|
name: Image Classification
|
|
type: image-classification
|
|
dataset:
|
|
name: imagenet-1k
|
|
type: imagenet-1k
|
|
config: default
|
|
split: validation
|
|
args: default
|
|
metrics:
|
|
- name: Accuracy
|
|
type: accuracy
|
|
value: 0.817
|
|
---
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
should probably proofread and complete it, then remove this comment. -->
|
|
|
|
# vit-base-patch16-224-finetuned-eurosat
|
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagenet-1k dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.6981
|
|
- Accuracy: 0.817
|
|
|
|
## 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: 3
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 0.8014 | 1.0 | 10009 | 0.7430 | 0.8052 |
|
|
| 0.6591 | 2.0 | 20018 | 0.7097 | 0.8132 |
|
|
| 0.562 | 3.0 | 30027 | 0.6981 | 0.817 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.39.3
|
|
- Pytorch 2.2.2+cu118
|
|
- Datasets 2.19.1
|
|
- Tokenizers 0.15.2
|
|
|