metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-finetuned_swinv2tiny-autotags-256
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: 0.965482233502538
swinv2-tiny-patch4-window8-256-finetuned_swinv2tiny-autotags-256
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1115
- Accuracy: 0.9655
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6169 | 0.99 | 61 | 1.1018 | 0.6701 |
| 0.7747 | 1.99 | 122 | 0.4571 | 0.8670 |
| 0.6088 | 2.99 | 183 | 0.3002 | 0.9198 |
| 0.3908 | 3.99 | 244 | 0.2334 | 0.9299 |
| 0.399 | 4.99 | 305 | 0.2138 | 0.9320 |
| 0.2969 | 5.99 | 366 | 0.1650 | 0.9492 |
| 0.2743 | 6.99 | 427 | 0.1514 | 0.9533 |
| 0.2947 | 7.99 | 488 | 0.1428 | 0.9513 |
| 0.2304 | 8.99 | 549 | 0.1541 | 0.9523 |
| 0.1957 | 9.99 | 610 | 0.1256 | 0.9604 |
| 0.1645 | 10.99 | 671 | 0.1138 | 0.9645 |
| 0.2317 | 11.99 | 732 | 0.1140 | 0.9655 |
| 0.1001 | 12.99 | 793 | 0.1068 | 0.9706 |
| 0.1564 | 13.99 | 854 | 0.1119 | 0.9675 |
| 0.1386 | 14.99 | 915 | 0.1115 | 0.9655 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.10.2+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2