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---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold4
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: 0.42384823848238484
---
<!-- 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. -->
# Boya1_SGD_1-e3_20Epoch_Deit-tiny-patch16_fold4
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7238
- Accuracy: 0.4238
## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4152 | 1.0 | 923 | 2.4593 | 0.2073 |
| 2.4387 | 2.0 | 1846 | 2.2993 | 0.2512 |
| 2.1969 | 3.0 | 2769 | 2.1607 | 0.3133 |
| 2.0455 | 4.0 | 3692 | 2.0589 | 0.3320 |
| 1.8171 | 5.0 | 4615 | 1.9845 | 0.3585 |
| 1.8796 | 6.0 | 5538 | 1.9302 | 0.3656 |
| 1.8281 | 7.0 | 6461 | 1.8840 | 0.3816 |
| 1.7455 | 8.0 | 7384 | 1.8500 | 0.3883 |
| 1.7072 | 9.0 | 8307 | 1.8232 | 0.4003 |
| 1.7401 | 10.0 | 9230 | 1.8005 | 0.4046 |
| 1.8157 | 11.0 | 10153 | 1.7845 | 0.4114 |
| 1.796 | 12.0 | 11076 | 1.7690 | 0.4114 |
| 1.7335 | 13.0 | 11999 | 1.7588 | 0.4122 |
| 1.6292 | 14.0 | 12922 | 1.7473 | 0.4190 |
| 1.7133 | 15.0 | 13845 | 1.7397 | 0.4222 |
| 1.7521 | 16.0 | 14768 | 1.7345 | 0.4195 |
| 1.8322 | 17.0 | 15691 | 1.7291 | 0.4244 |
| 1.7763 | 18.0 | 16614 | 1.7260 | 0.4244 |
| 1.5996 | 19.0 | 17537 | 1.7248 | 0.4225 |
| 1.6259 | 20.0 | 18460 | 1.7238 | 0.4238 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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