metadata
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: ktp-spoof-clip
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9852941176470589
ktp-spoof-clip
This model is a fine-tuned version of openai/clip-vit-base-patch32 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0740
- Accuracy: 0.9853
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 |
|---|---|---|---|---|
| No log | 0.8889 | 4 | 0.5501 | 0.8088 |
| No log | 2.0 | 9 | 0.3671 | 0.8529 |
| 0.5611 | 2.8889 | 13 | 0.3852 | 0.8235 |
| 0.5611 | 4.0 | 18 | 0.2422 | 0.9118 |
| 0.4558 | 4.8889 | 22 | 0.3534 | 0.8824 |
| 0.4558 | 6.0 | 27 | 0.1137 | 0.9412 |
| 0.3562 | 6.8889 | 31 | 0.5266 | 0.7941 |
| 0.3562 | 8.0 | 36 | 0.1918 | 0.9118 |
| 0.1201 | 8.8889 | 40 | 0.0301 | 1.0 |
| 0.1201 | 10.0 | 45 | 0.0450 | 0.9853 |
| 0.1201 | 10.8889 | 49 | 0.0327 | 0.9853 |
| 0.0604 | 12.0 | 54 | 0.0898 | 0.9706 |
| 0.0604 | 12.8889 | 58 | 0.0789 | 0.9853 |
| 0.0322 | 13.3333 | 60 | 0.0740 | 0.9853 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1