File size: 2,232 Bytes
3916d48 | 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 | ---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224
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: 0.6845918083031485
---
<!-- 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
This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8630
- Accuracy: 0.6846
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3586 | 1.0 | 252 | 1.2051 | 0.5403 |
| 1.2281 | 2.0 | 505 | 1.0535 | 0.6108 |
| 1.148 | 3.0 | 757 | 0.9985 | 0.6194 |
| 1.087 | 4.0 | 1010 | 0.9658 | 0.6361 |
| 1.1121 | 5.0 | 1262 | 0.9203 | 0.6539 |
| 1.0127 | 6.0 | 1515 | 0.9245 | 0.6567 |
| 0.9858 | 7.0 | 1767 | 0.8846 | 0.6757 |
| 0.9948 | 8.0 | 2020 | 0.8793 | 0.6748 |
| 0.9398 | 9.0 | 2272 | 0.8671 | 0.6765 |
| 0.9904 | 9.98 | 2520 | 0.8630 | 0.6846 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|