---
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
model-index:
- name: clip-finetuned-csu-p14-336-e4l58-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-e4l58-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: 0.7743

## 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: 1.2009578191195431e-08
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.4588        | 0.0921 | 500   | 1.4195          |
| 0.4255        | 0.1842 | 1000  | 1.3417          |
| 0.3724        | 0.2763 | 1500  | 1.2873          |
| 0.3251        | 0.3684 | 2000  | 1.2349          |
| 0.3308        | 0.4605 | 2500  | 1.1945          |
| 0.3017        | 0.5526 | 3000  | 1.1593          |
| 0.2962        | 0.6447 | 3500  | 1.1259          |
| 0.2919        | 0.7368 | 4000  | 1.0954          |
| 0.307         | 0.8289 | 4500  | 1.0729          |
| 0.2764        | 0.9210 | 5000  | 1.0524          |
| 0.2456        | 1.0131 | 5500  | 1.0375          |
| 0.2642        | 1.1052 | 6000  | 1.0233          |
| 0.2066        | 1.1973 | 6500  | 1.0104          |
| 0.2376        | 1.2894 | 7000  | 0.9984          |
| 0.1931        | 1.3815 | 7500  | 0.9887          |
| 0.2163        | 1.4736 | 8000  | 0.9767          |
| 0.1903        | 1.5657 | 8500  | 0.9665          |
| 0.2069        | 1.6578 | 9000  | 0.9572          |
| 0.2093        | 1.7499 | 9500  | 0.9497          |
| 0.2523        | 1.8420 | 10000 | 0.9420          |
| 0.2127        | 1.9341 | 10500 | 0.9329          |
| 0.1968        | 2.0262 | 11000 | 0.9270          |
| 0.1879        | 2.1183 | 11500 | 0.9231          |
| 0.1981        | 2.2104 | 12000 | 0.9184          |
| 0.1964        | 2.3024 | 12500 | 0.9135          |
| 0.1697        | 2.3945 | 13000 | 0.9100          |
| 0.2015        | 2.4866 | 13500 | 0.9052          |
| 0.1827        | 2.5787 | 14000 | 0.9026          |
| 0.1435        | 2.6708 | 14500 | 0.8998          |
| 0.1541        | 2.7629 | 15000 | 0.8963          |
| 0.1716        | 2.8550 | 15500 | 0.8935          |
| 0.2056        | 2.9471 | 16000 | 0.8905          |
| 0.1843        | 3.0392 | 16500 | 0.8875          |
| 0.1611        | 3.1313 | 17000 | 0.8858          |
| 0.1568        | 3.2240 | 17500 | 0.7821          |
| 0.1395        | 3.3161 | 18000 | 0.7794          |
| 0.1804        | 3.4083 | 18500 | 0.7778          |
| 0.1728        | 3.5004 | 19000 | 0.7769          |
| 0.179         | 3.5925 | 19500 | 0.7758          |
| 0.179         | 3.6846 | 20000 | 0.7752          |
| 0.1454        | 3.7767 | 20500 | 0.7747          |
| 0.1568        | 3.8688 | 21000 | 0.7744          |
| 0.1663        | 3.9609 | 21500 | 0.7743          |


### Framework versions

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