---
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