metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
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: 0.9310344827586207
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: 0.2606
- Accuracy: 0.9310
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 | 0.89 | 6 | 1.0179 | 0.5862 |
| 0.9897 | 1.93 | 13 | 0.7600 | 0.7241 |
| 0.5848 | 2.96 | 20 | 0.8368 | 0.5862 |
| 0.5848 | 4.0 | 27 | 0.4708 | 0.8621 |
| 0.2747 | 4.89 | 33 | 0.3727 | 0.8966 |
| 0.2259 | 5.93 | 40 | 0.3100 | 0.9310 |
| 0.2259 | 6.96 | 47 | 0.2294 | 0.9310 |
| 0.1596 | 8.0 | 54 | 0.2631 | 0.8966 |
| 0.1844 | 8.89 | 60 | 0.2606 | 0.9310 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3