File size: 2,441 Bytes
49546c8 45f229b 49546c8 45f229b 49546c8 45f229b 49546c8 |
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: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finalterm
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: 0.9326287978863936
---
<!-- 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-finalterm
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: 0.1890
- Accuracy: 0.9326
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.2544 | 0.9684 | 23 | 0.5278 | 0.8692 |
| 0.3694 | 1.9789 | 47 | 0.2528 | 0.9049 |
| 0.2816 | 2.9895 | 71 | 0.2065 | 0.9234 |
| 0.2292 | 4.0 | 95 | 0.1986 | 0.9247 |
| 0.2193 | 4.9684 | 118 | 0.1991 | 0.9168 |
| 0.2286 | 5.9789 | 142 | 0.1913 | 0.9339 |
| 0.1887 | 6.9895 | 166 | 0.1932 | 0.9247 |
| 0.1905 | 8.0 | 190 | 0.1883 | 0.9287 |
| 0.1692 | 8.9684 | 213 | 0.1891 | 0.9326 |
| 0.1767 | 9.6842 | 230 | 0.1890 | 0.9326 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|