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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_fold3
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: 0.42884199134199136
---
<!-- 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_fold3
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: 1.7155
- Accuracy: 0.4288
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4106 | 1.0 | 923 | 2.4578 | 0.2002 |
| 2.3587 | 2.0 | 1846 | 2.2972 | 0.2516 |
| 2.1274 | 3.0 | 2769 | 2.1627 | 0.3055 |
| 2.1583 | 4.0 | 3692 | 2.0604 | 0.3279 |
| 1.9036 | 5.0 | 4615 | 1.9842 | 0.3458 |
| 1.7721 | 6.0 | 5538 | 1.9243 | 0.3582 |
| 1.9867 | 7.0 | 6461 | 1.8782 | 0.3726 |
| 1.8532 | 8.0 | 7384 | 1.8428 | 0.3891 |
| 1.8503 | 9.0 | 8307 | 1.8165 | 0.4004 |
| 1.79 | 10.0 | 9230 | 1.7943 | 0.4037 |
| 1.7717 | 11.0 | 10153 | 1.7761 | 0.4091 |
| 1.7696 | 12.0 | 11076 | 1.7613 | 0.4148 |
| 1.7298 | 13.0 | 11999 | 1.7507 | 0.4191 |
| 1.7468 | 14.0 | 12922 | 1.7401 | 0.4210 |
| 1.6085 | 15.0 | 13845 | 1.7322 | 0.4229 |
| 1.7188 | 16.0 | 14768 | 1.7257 | 0.4278 |
| 1.7307 | 17.0 | 15691 | 1.7212 | 0.4259 |
| 1.5257 | 18.0 | 16614 | 1.7177 | 0.4275 |
| 1.6729 | 19.0 | 17537 | 1.7160 | 0.4294 |
| 1.7293 | 20.0 | 18460 | 1.7155 | 0.4288 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1
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