|
---
|
|
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_fold2
|
|
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: 0.4181081081081081
|
|
---
|
|
|
|
<!-- 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_fold2
|
|
|
|
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: 1.7360
|
|
- Accuracy: 0.4181
|
|
|
|
## 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 |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 2.448 | 1.0 | 923 | 2.4582 | 0.2016 |
|
|
| 2.3582 | 2.0 | 1846 | 2.3021 | 0.2376 |
|
|
| 2.2617 | 3.0 | 2769 | 2.1666 | 0.2897 |
|
|
| 2.0757 | 4.0 | 3692 | 2.0662 | 0.3235 |
|
|
| 2.008 | 5.0 | 4615 | 1.9944 | 0.3449 |
|
|
| 2.0395 | 6.0 | 5538 | 1.9375 | 0.3595 |
|
|
| 1.9087 | 7.0 | 6461 | 1.8952 | 0.3749 |
|
|
| 1.9463 | 8.0 | 7384 | 1.8644 | 0.3805 |
|
|
| 1.8879 | 9.0 | 8307 | 1.8376 | 0.3908 |
|
|
| 1.7446 | 10.0 | 9230 | 1.8140 | 0.3938 |
|
|
| 1.7618 | 11.0 | 10153 | 1.7964 | 0.3965 |
|
|
| 1.7616 | 12.0 | 11076 | 1.7817 | 0.4051 |
|
|
| 1.7296 | 13.0 | 11999 | 1.7702 | 0.4057 |
|
|
| 1.8498 | 14.0 | 12922 | 1.7608 | 0.4124 |
|
|
| 1.7605 | 15.0 | 13845 | 1.7532 | 0.4111 |
|
|
| 1.7119 | 16.0 | 14768 | 1.7468 | 0.4154 |
|
|
| 1.7061 | 17.0 | 15691 | 1.7421 | 0.4157 |
|
|
| 1.6731 | 18.0 | 16614 | 1.7387 | 0.4178 |
|
|
| 1.5776 | 19.0 | 17537 | 1.7366 | 0.4189 |
|
|
| 1.5522 | 20.0 | 18460 | 1.7360 | 0.4181 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.40.1
|
|
- Pytorch 2.1.0
|
|
- Datasets 2.19.0
|
|
- Tokenizers 0.19.1
|
|
|
