File size: 2,432 Bytes
f09903c 973382c f09903c 838d3a3 f09903c 973382c f09903c 838d3a3 f09903c 13bdcfd f09903c 838d3a3 f09903c e7db2c6 f09903c e7db2c6 f09903c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
---
license: apache-2.0
base_model: mansee/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-img_orientation
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: 0.9644592530889907
---
<!-- 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. -->
# swin-tiny-patch4-window7-224-img_orientation
This model is a fine-tuned version of [mansee/swin-tiny-patch4-window7-224](https://huggingface.co/mansee/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1069
- Accuracy: 0.9645
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5605 | 1.0 | 506 | 0.3984 | 0.8341 |
| 0.3828 | 2.0 | 1013 | 0.1944 | 0.9271 |
| 0.3092 | 3.0 | 1519 | 0.1862 | 0.9339 |
| 0.3234 | 4.0 | 2026 | 0.1415 | 0.9510 |
| 0.2471 | 5.0 | 2532 | 0.1355 | 0.9517 |
| 0.251 | 6.0 | 3039 | 0.1170 | 0.9606 |
| 0.2276 | 7.0 | 3545 | 0.1136 | 0.9627 |
| 0.2182 | 8.0 | 4052 | 0.1121 | 0.9628 |
| 0.1386 | 9.0 | 4558 | 0.1116 | 0.9632 |
| 0.1466 | 9.99 | 5060 | 0.1069 | 0.9645 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|