metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: segformer-class-classWeights-augmentation
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: 0.9772727272727273
segformer-class-classWeights-augmentation
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0991
- Accuracy: 0.9773
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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- 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 |
|---|---|---|---|---|
| No log | 0.96 | 6 | 1.0191 | 0.6364 |
| 1.0551 | 1.92 | 12 | 0.8644 | 0.7273 |
| 1.0551 | 2.88 | 18 | 0.5563 | 0.8636 |
| 0.7192 | 4.0 | 25 | 0.2687 | 0.9545 |
| 0.4056 | 4.96 | 31 | 0.1921 | 0.9545 |
| 0.4056 | 5.92 | 37 | 0.1246 | 0.9545 |
| 0.267 | 6.88 | 43 | 0.1010 | 0.9773 |
| 0.2547 | 8.0 | 50 | 0.1442 | 0.9773 |
| 0.2547 | 8.96 | 56 | 0.1188 | 0.9773 |
| 0.189 | 9.6 | 60 | 0.0991 | 0.9773 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3