---
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
model-index:
- name: clip-finetuned-csu-p14-336-e3l55-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-e3l55-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: 1.9056

## 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: 8.810707926567202e-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: 3.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.7336        | 0.0921 | 500   | 2.0781          |
| 0.6953        | 0.1842 | 1000  | 2.0783          |
| 0.6953        | 0.2763 | 1500  | 2.0777          |
| 0.6932        | 0.3684 | 2000  | 2.0722          |
| 0.6907        | 0.4605 | 2500  | 2.0792          |
| 0.7043        | 0.5526 | 3000  | 2.0205          |
| 0.7078        | 0.6447 | 3500  | 2.1256          |
| 0.7034        | 0.7368 | 4000  | 2.0000          |
| 0.6671        | 0.8289 | 4500  | 2.1608          |
| 0.6899        | 0.9210 | 5000  | 2.0940          |
| 0.6649        | 1.0131 | 5500  | 1.9776          |
| 0.6748        | 1.1052 | 6000  | 1.9852          |
| 0.6456        | 1.1973 | 6500  | 1.9981          |
| 0.6514        | 1.2894 | 7000  | 1.9637          |
| 0.6179        | 1.3815 | 7500  | 2.0034          |
| 0.6561        | 1.4736 | 8000  | 2.2865          |
| 0.6328        | 1.5657 | 8500  | 2.4808          |
| 0.7053        | 1.6578 | 9000  | 2.1610          |
| 0.6533        | 1.7499 | 9500  | 1.9845          |
| 0.6594        | 1.8420 | 10000 | 1.9895          |
| 0.6597        | 1.9341 | 10500 | 2.0103          |
| 0.6435        | 2.0262 | 11000 | 2.0589          |
| 0.6404        | 2.1183 | 11500 | 2.0517          |
| 0.6348        | 2.2104 | 12000 | 1.9749          |
| 0.6545        | 2.3024 | 12500 | 1.9681          |
| 0.6323        | 2.3945 | 13000 | 1.9056          |
| 0.6045        | 2.4866 | 13500 | 1.9470          |
| 0.6492        | 2.5787 | 14000 | 2.0177          |
| 0.6512        | 2.6708 | 14500 | 1.9483          |
| 0.6382        | 2.7629 | 15000 | 1.9499          |
| 0.6203        | 2.8550 | 15500 | 1.9529          |
| 0.6241        | 2.9471 | 16000 | 1.9817          |


### Framework versions

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