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---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: 2D_hgg_lgg_classification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8203125
---
<!-- 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. -->
# 2D_hgg_lgg_classification
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7560
- Accuracy: 0.8203
## 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.7243 | 0.9655 | 7 | 0.6272 | 0.7656 |
| 0.5807 | 1.9310 | 14 | 0.5266 | 0.7812 |
| 0.556 | 2.8966 | 21 | 0.5086 | 0.7812 |
| 0.4675 | 4.0 | 29 | 0.4844 | 0.7812 |
| 0.4992 | 4.9655 | 36 | 0.4664 | 0.7812 |
| 0.4562 | 5.9310 | 43 | 0.4430 | 0.7344 |
| 0.4344 | 6.8966 | 50 | 0.4726 | 0.7109 |
| 0.3778 | 8.0 | 58 | 0.4302 | 0.7656 |
| 0.3922 | 8.9655 | 65 | 0.4350 | 0.8125 |
| 0.3864 | 9.9310 | 72 | 0.4259 | 0.7656 |
| 0.3388 | 10.8966 | 79 | 0.4462 | 0.7656 |
| 0.3071 | 12.0 | 87 | 0.5272 | 0.7969 |
| 0.3233 | 12.9655 | 94 | 0.4723 | 0.7188 |
| 0.3103 | 13.9310 | 101 | 0.4494 | 0.7656 |
| 0.2818 | 14.8966 | 108 | 0.4279 | 0.8047 |
| 0.2341 | 16.0 | 116 | 0.4069 | 0.7891 |
| 0.2103 | 16.9655 | 123 | 0.4237 | 0.7969 |
| 0.219 | 17.9310 | 130 | 0.4467 | 0.8047 |
| 0.21 | 18.8966 | 137 | 0.4380 | 0.7812 |
| 0.1994 | 20.0 | 145 | 0.4629 | 0.7969 |
| 0.1865 | 20.9655 | 152 | 0.5012 | 0.7891 |
| 0.1872 | 21.9310 | 159 | 0.5055 | 0.8203 |
| 0.2144 | 22.8966 | 166 | 0.6089 | 0.8125 |
| 0.1737 | 24.0 | 174 | 0.4914 | 0.7969 |
| 0.1633 | 24.9655 | 181 | 0.5137 | 0.7812 |
| 0.1624 | 25.9310 | 188 | 0.5985 | 0.7812 |
| 0.1525 | 26.8966 | 195 | 0.5090 | 0.8047 |
| 0.136 | 28.0 | 203 | 0.5170 | 0.8125 |
| 0.1451 | 28.9655 | 210 | 0.6165 | 0.8203 |
| 0.1405 | 29.9310 | 217 | 0.6124 | 0.7969 |
| 0.1384 | 30.8966 | 224 | 0.5578 | 0.8047 |
| 0.1246 | 32.0 | 232 | 0.5967 | 0.8125 |
| 0.1371 | 32.9655 | 239 | 0.6135 | 0.7812 |
| 0.1111 | 33.9310 | 246 | 0.6878 | 0.8047 |
| 0.1305 | 34.8966 | 253 | 0.7300 | 0.8125 |
| 0.1124 | 36.0 | 261 | 0.6687 | 0.8203 |
| 0.1214 | 36.9655 | 268 | 0.6692 | 0.8047 |
| 0.1065 | 37.9310 | 275 | 0.7058 | 0.8125 |
| 0.1183 | 38.8966 | 282 | 0.6884 | 0.7969 |
| 0.0928 | 40.0 | 290 | 0.7104 | 0.7969 |
| 0.1248 | 40.9655 | 297 | 0.6961 | 0.7969 |
| 0.0949 | 41.9310 | 304 | 0.7265 | 0.8203 |
| 0.1048 | 42.8966 | 311 | 0.7430 | 0.8281 |
| 0.0887 | 44.0 | 319 | 0.7627 | 0.8047 |
| 0.0866 | 44.9655 | 326 | 0.7483 | 0.8203 |
| 0.0978 | 45.9310 | 333 | 0.7515 | 0.8125 |
| 0.0901 | 46.8966 | 340 | 0.7518 | 0.8125 |
| 0.0785 | 48.0 | 348 | 0.7557 | 0.8203 |
| 0.0747 | 48.2759 | 350 | 0.7560 | 0.8203 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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