---
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
model-index:
- name: clip-finetuned-csu-p14-336-e4l57-l
  results: []
---

<!-- 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. -->

# clip-finetuned-csu-p14-336-e4l57-l

This model is a fine-tuned version of [openai/clip-vit-large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1766

## 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-07
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.271         | 0.0921 | 500   | 1.0693          |
| 0.2493        | 0.1842 | 1000  | 0.9427          |
| 0.2348        | 0.2763 | 1500  | 0.8727          |
| 0.1552        | 0.3685 | 2000  | 0.8326          |
| 0.1753        | 0.4606 | 2500  | 0.7550          |
| 0.1659        | 0.5527 | 3000  | 0.7192          |
| 0.105         | 0.6448 | 3500  | 0.7118          |
| 0.1336        | 0.7369 | 4000  | 0.6953          |
| 0.1154        | 0.8290 | 4500  | 0.6745          |
| 0.108         | 0.9211 | 5000  | 0.6560          |
| 0.1106        | 1.0133 | 5500  | 0.6367          |
| 0.0591        | 1.1054 | 6000  | 0.6259          |
| 0.0745        | 1.1975 | 6500  | 0.6210          |
| 0.0502        | 1.2896 | 7000  | 0.6133          |
| 0.079         | 1.3817 | 7500  | 0.6007          |
| 0.0776        | 1.4738 | 8000  | 0.5866          |
| 0.0492        | 1.5660 | 8500  | 0.5679          |
| 0.0794        | 1.6581 | 9000  | 0.5762          |
| 0.0677        | 1.7502 | 9500  | 0.5566          |
| 0.0566        | 1.8423 | 10000 | 0.5482          |
| 0.0828        | 1.9344 | 10500 | 0.5500          |
| 0.0573        | 2.0265 | 11000 | 0.5342          |
| 0.0401        | 2.1186 | 11500 | 0.5351          |
| 0.0152        | 2.2108 | 12000 | 0.5349          |
| 0.0638        | 2.3029 | 12500 | 0.5318          |
| 0.0488        | 2.3950 | 13000 | 0.5306          |
| 0.0456        | 2.4871 | 13500 | 0.5211          |
| 0.0264        | 2.5792 | 14000 | 0.5194          |
| 0.0381        | 2.6713 | 14500 | 0.5206          |
| 0.0413        | 2.7634 | 15000 | 0.5168          |
| 0.0392        | 2.8556 | 15500 | 0.5149          |
| 0.0352        | 2.9477 | 16000 | 0.5112          |
| 0.0467        | 3.0398 | 16500 | 0.5098          |
| 0.0366        | 3.1319 | 17000 | 0.5089          |
| 0.0454        | 3.2240 | 17500 | 0.5104          |
| 0.0209        | 3.3161 | 18000 | 0.5071          |
| 0.0636        | 3.4083 | 18500 | 0.5045          |
| 0.0159        | 3.5004 | 19000 | 0.5019          |
| 0.0303        | 3.5925 | 19500 | 0.4985          |
| 0.0353        | 3.6846 | 20000 | 0.4975          |
| 0.0261        | 3.7767 | 20500 | 0.4962          |
| 0.0291        | 3.8688 | 21000 | 0.4956          |
| 0.0338        | 3.9609 | 21500 | 0.4956          |
| 0.0432        | 3.6845 | 22000 | 0.1784          |
| 0.0461        | 3.7682 | 22500 | 0.1767          |
| 0.0513        | 3.8520 | 23000 | 0.1774          |
| 0.0326        | 3.9357 | 23500 | 0.1766          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 1.12.1
- Datasets 2.21.0
- Tokenizers 0.19.1