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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: xyz
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.785
---
<!-- 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. -->
# xyz
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9604
- Accuracy: 0.785
## 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: 0.0002
- train_batch_size: 48
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8634 | 0.55 | 100 | 0.9266 | 0.6975 |
| 0.3225 | 1.09 | 200 | 0.8994 | 0.7325 |
| 0.2353 | 1.64 | 300 | 0.9683 | 0.73 |
| 0.1119 | 2.19 | 400 | 0.9247 | 0.7492 |
| 0.049 | 2.73 | 500 | 0.9663 | 0.7567 |
| 0.0537 | 3.28 | 600 | 1.0558 | 0.7567 |
| 0.0274 | 3.83 | 700 | 1.0344 | 0.7692 |
| 0.0102 | 4.37 | 800 | 0.9259 | 0.7942 |
| 0.0095 | 4.92 | 900 | 0.9604 | 0.785 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
|