metadata
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-22k-224-finetuned-piid
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: val
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7853881278538812
convnextv2-tiny-22k-224-finetuned-piid
This model is a fine-tuned version of facebook/convnextv2-tiny-22k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6118
- Accuracy: 0.7854
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2083 | 0.98 | 20 | 1.0137 | 0.6027 |
| 0.6826 | 2.0 | 41 | 0.6901 | 0.6895 |
| 0.5161 | 2.98 | 61 | 0.6377 | 0.7078 |
| 0.4475 | 4.0 | 82 | 0.5423 | 0.7215 |
| 0.4325 | 4.98 | 102 | 0.5165 | 0.7671 |
| 0.3433 | 6.0 | 123 | 0.5916 | 0.7763 |
| 0.2677 | 6.98 | 143 | 0.5866 | 0.7534 |
| 0.2498 | 8.0 | 164 | 0.5146 | 0.7900 |
| 0.2387 | 8.98 | 184 | 0.5631 | 0.7580 |
| 0.2132 | 10.0 | 205 | 0.5320 | 0.7991 |
| 0.2178 | 10.98 | 225 | 0.5833 | 0.7854 |
| 0.1474 | 12.0 | 246 | 0.5902 | 0.7900 |
| 0.1627 | 12.98 | 266 | 0.6142 | 0.7808 |
| 0.1651 | 14.0 | 287 | 0.6063 | 0.7808 |
| 0.158 | 14.98 | 307 | 0.6130 | 0.7808 |
| 0.126 | 16.0 | 328 | 0.6647 | 0.7671 |
| 0.0821 | 16.98 | 348 | 0.5972 | 0.7808 |
| 0.1062 | 18.0 | 369 | 0.5975 | 0.7945 |
| 0.1031 | 18.98 | 389 | 0.6129 | 0.7808 |
| 0.1268 | 19.51 | 400 | 0.6118 | 0.7854 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3