metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_swin_imbalanced
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9678571428571429
weeds_swin_imbalanced
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1672
- Accuracy: 0.9679
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
---|---|---|---|---|
0.3442 | 1.0 | 275 | 0.3769 | 0.8857 |
0.2041 | 2.0 | 550 | 0.2455 | 0.925 |
0.1082 | 3.0 | 825 | 0.2683 | 0.9232 |
0.1195 | 4.0 | 1100 | 0.1772 | 0.9554 |
0.1083 | 5.0 | 1375 | 0.2039 | 0.9536 |
0.1674 | 6.0 | 1650 | 0.2055 | 0.9554 |
0.0882 | 7.0 | 1925 | 0.1931 | 0.9661 |
0.155 | 8.0 | 2200 | 0.3192 | 0.9375 |
0.0487 | 9.0 | 2475 | 0.1736 | 0.9679 |
0.1015 | 10.0 | 2750 | 0.1672 | 0.9679 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2