File size: 2,384 Bytes
6ba863a ceba481 6ba863a ceba481 6ba863a 804c535 6ba863a ceba481 6ba863a |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-mixed-bottoms
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: 0.9888682745825603
---
<!-- 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-mixed-bottoms
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: 0.0272
- Accuracy: 0.9889
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1479 | 0.99 | 86 | 0.1040 | 0.9592 |
| 0.145 | 2.0 | 173 | 0.1033 | 0.9592 |
| 0.1248 | 2.99 | 259 | 0.0640 | 0.9777 |
| 0.0667 | 4.0 | 346 | 0.0378 | 0.9907 |
| 0.0826 | 4.99 | 432 | 0.0400 | 0.9814 |
| 0.0635 | 6.0 | 519 | 0.0331 | 0.9907 |
| 0.0688 | 7.0 | 606 | 0.0461 | 0.9852 |
| 0.0549 | 7.99 | 692 | 0.0335 | 0.9889 |
| 0.0501 | 9.0 | 779 | 0.0241 | 0.9907 |
| 0.0434 | 9.93 | 860 | 0.0272 | 0.9889 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
|