metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-tiny-patch16-224-finetuned-papsmear
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: 0.8529411764705882
deit-tiny-patch16-224-finetuned-papsmear
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4389
- Accuracy: 0.8529
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 |
|---|---|---|---|---|
| 1.8247 | 0.9870 | 19 | 1.6199 | 0.3015 |
| 1.415 | 1.9740 | 38 | 1.2594 | 0.5147 |
| 1.06 | 2.9610 | 57 | 1.0316 | 0.6471 |
| 0.8808 | 4.0 | 77 | 1.0088 | 0.625 |
| 0.7646 | 4.9870 | 96 | 0.8211 | 0.6985 |
| 0.6798 | 5.9740 | 115 | 0.7383 | 0.7132 |
| 0.554 | 6.9610 | 134 | 0.6477 | 0.7574 |
| 0.5358 | 8.0 | 154 | 0.5824 | 0.7647 |
| 0.4689 | 8.9870 | 173 | 0.5571 | 0.7794 |
| 0.4217 | 9.9740 | 192 | 0.5506 | 0.7868 |
| 0.4063 | 10.9610 | 211 | 0.4987 | 0.8235 |
| 0.3827 | 12.0 | 231 | 0.4793 | 0.8088 |
| 0.3095 | 12.9870 | 250 | 0.4724 | 0.8015 |
| 0.3521 | 13.9740 | 269 | 0.4389 | 0.8529 |
| 0.3397 | 14.8052 | 285 | 0.4383 | 0.8456 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1