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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: 1.0
---
<!-- 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: 0.0312
- Accuracy: 1.0
## 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 | 0.8696 | 5 | 0.5871 | 0.7 |
| No log | 1.9130 | 11 | 0.0729 | 0.9667 |
| 0.7676 | 2.9565 | 17 | 0.1986 | 0.9 |
| 0.7676 | 4.0 | 23 | 0.1610 | 0.9 |
| 0.7676 | 4.8696 | 28 | 0.0644 | 0.9667 |
| 0.2441 | 5.9130 | 34 | 0.2016 | 0.9 |
| 0.2441 | 6.9565 | 40 | 0.1530 | 0.9 |
| 0.1751 | 8.0 | 46 | 0.0412 | 1.0 |
| 0.1751 | 8.8696 | 51 | 0.0301 | 1.0 |
| 0.1751 | 9.9130 | 57 | 0.0495 | 0.9667 |
| 0.1156 | 10.9565 | 63 | 0.0283 | 1.0 |
| 0.1156 | 12.0 | 69 | 0.0214 | 1.0 |
| 0.1156 | 12.8696 | 74 | 0.1014 | 0.9667 |
| 0.1238 | 13.9130 | 80 | 0.0538 | 1.0 |
| 0.1238 | 14.9565 | 86 | 0.0477 | 1.0 |
| 0.1064 | 16.0 | 92 | 0.0105 | 1.0 |
| 0.1064 | 16.8696 | 97 | 0.0389 | 0.9667 |
| 0.1064 | 17.9130 | 103 | 0.0120 | 1.0 |
| 0.0862 | 18.9565 | 109 | 0.0183 | 1.0 |
| 0.0862 | 20.0 | 115 | 0.0259 | 1.0 |
| 0.0345 | 20.8696 | 120 | 0.0272 | 1.0 |
| 0.0345 | 21.7391 | 125 | 0.0312 | 1.0 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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