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---
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: document-spoof
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: 0.9767441860465116
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# document-spoof
This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1105
- Accuracy: 0.9767
## 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: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.9524 | 5 | 0.5211 | 0.8837 |
| No log | 1.9048 | 10 | 0.2271 | 0.8837 |
| 0.545 | 2.8571 | 15 | 0.0975 | 0.9884 |
| 0.545 | 4.0 | 21 | 0.1020 | 0.9767 |
| 0.545 | 4.9524 | 26 | 0.3087 | 0.9535 |
| 0.472 | 5.9048 | 31 | 0.3385 | 0.8023 |
| 0.472 | 6.8571 | 36 | 0.2358 | 0.8605 |
| 0.472 | 8.0 | 42 | 0.3675 | 0.8605 |
| 0.3762 | 8.9524 | 47 | 0.1460 | 0.9535 |
| 0.3762 | 9.9048 | 52 | 0.6158 | 0.8140 |
| 0.3762 | 10.8571 | 57 | 0.3228 | 0.9186 |
| 0.1586 | 12.0 | 63 | 0.0248 | 0.9884 |
| 0.1586 | 12.9524 | 68 | 0.0639 | 0.9651 |
| 0.1586 | 13.9048 | 73 | 0.5674 | 0.8488 |
| 0.1159 | 14.8571 | 78 | 0.0291 | 0.9884 |
| 0.1159 | 16.0 | 84 | 0.0539 | 0.9884 |
| 0.1159 | 16.9524 | 89 | 0.0772 | 0.9767 |
| 0.0366 | 17.9048 | 94 | 0.0031 | 1.0 |
| 0.0366 | 18.8571 | 99 | 0.1506 | 0.9535 |
| 0.0179 | 20.0 | 105 | 0.0007 | 1.0 |
| 0.0179 | 20.9524 | 110 | 0.1427 | 0.9535 |
| 0.0179 | 21.9048 | 115 | 0.2299 | 0.9419 |
| 0.0036 | 22.8571 | 120 | 0.1373 | 0.9767 |
| 0.0036 | 23.8095 | 125 | 0.1105 | 0.9767 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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