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---
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: ktp-kk-crop
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: 0.945054945054945
---
<!-- 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. -->
# ktp-kk-crop
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: 0.2528
- Accuracy: 0.9451
## 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 | 0.9655 | 7 | 0.5985 | 0.6154 |
| No log | 1.9310 | 14 | 0.1681 | 0.9341 |
| 0.4711 | 2.8966 | 21 | 0.2271 | 0.9011 |
| 0.4711 | 4.0 | 29 | 0.8009 | 0.7473 |
| 0.3768 | 4.9655 | 36 | 0.1365 | 0.9560 |
| 0.3768 | 5.9310 | 43 | 0.1176 | 0.9780 |
| 0.069 | 6.8966 | 50 | 0.0880 | 0.9890 |
| 0.069 | 8.0 | 58 | 0.6839 | 0.9011 |
| 0.0212 | 8.9655 | 65 | 0.3376 | 0.9451 |
| 0.0212 | 9.9310 | 72 | 0.2240 | 0.9670 |
| 0.0201 | 10.8966 | 79 | 0.5612 | 0.9341 |
| 0.0201 | 12.0 | 87 | 0.2688 | 0.9560 |
| 0.0039 | 12.9655 | 94 | 0.1710 | 0.9780 |
| 0.0039 | 13.9310 | 101 | 0.3437 | 0.9560 |
| 0.0293 | 14.8966 | 108 | 0.2446 | 0.9670 |
| 0.0293 | 16.0 | 116 | 0.1507 | 0.9780 |
| 0.0009 | 16.9655 | 123 | 0.2032 | 0.9670 |
| 0.0009 | 17.9310 | 130 | 0.2481 | 0.9451 |
| 0.0 | 18.8966 | 137 | 0.2608 | 0.9451 |
| 0.0 | 20.0 | 145 | 0.2611 | 0.9451 |
| 0.0 | 20.9655 | 152 | 0.2579 | 0.9451 |
| 0.0 | 21.9310 | 159 | 0.2554 | 0.9451 |
| 0.0 | 22.8966 | 166 | 0.2536 | 0.9451 |
| 0.0 | 24.0 | 174 | 0.2528 | 0.9451 |
| 0.0 | 24.1379 | 175 | 0.2528 | 0.9451 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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