metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: delivery_truck_classification
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: 1
delivery_truck_classification
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: 0.2027
- Accuracy: 1.0
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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 1.6169 | 0.4286 |
| No log | 2.0 | 2 | 1.5622 | 0.5 |
| No log | 3.0 | 3 | 1.4656 | 0.5714 |
| No log | 4.0 | 4 | 1.3434 | 0.7143 |
| No log | 5.0 | 5 | 1.1958 | 0.8571 |
| No log | 6.0 | 6 | 1.0398 | 0.8571 |
| No log | 7.0 | 7 | 0.8839 | 0.8571 |
| No log | 8.0 | 8 | 0.7458 | 0.8571 |
| No log | 9.0 | 9 | 0.6267 | 0.8571 |
| No log | 10.0 | 10 | 0.5253 | 0.8571 |
| No log | 11.0 | 11 | 0.4414 | 0.8571 |
| No log | 12.0 | 12 | 0.3764 | 0.8571 |
| No log | 13.0 | 13 | 0.3250 | 0.8571 |
| No log | 14.0 | 14 | 0.2810 | 0.8571 |
| No log | 15.0 | 15 | 0.2406 | 0.9286 |
| No log | 16.0 | 16 | 0.2027 | 1.0 |
| No log | 17.0 | 17 | 0.1679 | 1.0 |
| No log | 18.0 | 18 | 0.1376 | 1.0 |
| No log | 19.0 | 19 | 0.1119 | 1.0 |
| 1.0444 | 20.0 | 20 | 0.0910 | 1.0 |
| 1.0444 | 21.0 | 21 | 0.0734 | 1.0 |
| 1.0444 | 22.0 | 22 | 0.0616 | 1.0 |
| 1.0444 | 23.0 | 23 | 0.0536 | 1.0 |
| 1.0444 | 24.0 | 24 | 0.0478 | 1.0 |
| 1.0444 | 25.0 | 25 | 0.0437 | 1.0 |
| 1.0444 | 26.0 | 26 | 0.0414 | 1.0 |
| 1.0444 | 27.0 | 27 | 0.0376 | 1.0 |
| 1.0444 | 28.0 | 28 | 0.0342 | 1.0 |
| 1.0444 | 29.0 | 29 | 0.0313 | 1.0 |
| 1.0444 | 30.0 | 30 | 0.0287 | 1.0 |
| 1.0444 | 31.0 | 31 | 0.0274 | 1.0 |
| 1.0444 | 32.0 | 32 | 0.0267 | 1.0 |
| 1.0444 | 33.0 | 33 | 0.0263 | 1.0 |
| 1.0444 | 34.0 | 34 | 0.0260 | 1.0 |
| 1.0444 | 35.0 | 35 | 0.0258 | 1.0 |
| 1.0444 | 36.0 | 36 | 0.0255 | 1.0 |
| 1.0444 | 37.0 | 37 | 0.0249 | 1.0 |
| 1.0444 | 38.0 | 38 | 0.0246 | 1.0 |
| 1.0444 | 39.0 | 39 | 0.0243 | 1.0 |
| 0.3497 | 40.0 | 40 | 0.0240 | 1.0 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1