---
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
model-index:
- name: clip-finetuned-csu-p14-336-e4l59-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-e4l59-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: 1.3460

## 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-09
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.3952        | 0.0921 | 500   | 1.4940          |
| 0.4562        | 0.1842 | 1000  | 1.4853          |
| 0.5131        | 0.2763 | 1500  | 1.4758          |
| 0.4481        | 0.3685 | 2000  | 1.4676          |
| 0.4839        | 0.4606 | 2500  | 1.4585          |
| 0.4377        | 0.5527 | 3000  | 1.4508          |
| 0.4231        | 0.6448 | 3500  | 1.4432          |
| 0.4369        | 0.7369 | 4000  | 1.4366          |
| 0.4082        | 0.8290 | 4500  | 1.4302          |
| 0.4234        | 0.9211 | 5000  | 1.4243          |
| 0.4266        | 1.0133 | 5500  | 1.4191          |
| 0.4438        | 1.1054 | 6000  | 1.4137          |
| 0.3814        | 1.1975 | 6500  | 1.4085          |
| 0.3327        | 1.2896 | 7000  | 1.4042          |
| 0.4045        | 1.3817 | 7500  | 1.3989          |
| 0.4038        | 1.4738 | 8000  | 1.3937          |
| 0.3659        | 1.5660 | 8500  | 1.3894          |
| 0.4282        | 1.6581 | 9000  | 1.3855          |
| 0.4173        | 1.7502 | 9500  | 1.3816          |
| 0.3758        | 1.8423 | 10000 | 1.3779          |
| 0.4105        | 1.9344 | 10500 | 1.3745          |
| 0.3765        | 2.0265 | 11000 | 1.3716          |
| 0.3746        | 2.1186 | 11500 | 1.3690          |
| 0.3783        | 2.2108 | 12000 | 1.3662          |
| 0.3832        | 2.3029 | 12500 | 1.3640          |
| 0.3984        | 2.3950 | 13000 | 1.3617          |
| 0.4124        | 2.4871 | 13500 | 1.3593          |
| 0.3363        | 2.5792 | 14000 | 1.3572          |
| 0.3274        | 2.6713 | 14500 | 1.3555          |
| 0.4039        | 2.7634 | 15000 | 1.3538          |
| 0.378         | 2.8556 | 15500 | 1.3524          |
| 0.3543        | 2.9477 | 16000 | 1.3511          |
| 0.3606        | 3.0398 | 16500 | 1.3501          |
| 0.4024        | 3.1319 | 17000 | 1.3491          |
| 0.3182        | 3.2240 | 17500 | 1.3482          |
| 0.3564        | 3.3161 | 18000 | 1.3475          |
| 0.3842        | 3.4083 | 18500 | 1.3470          |
| 0.352         | 3.5004 | 19000 | 1.3467          |
| 0.3828        | 3.5925 | 19500 | 1.3464          |
| 0.39          | 3.6846 | 20000 | 1.3462          |
| 0.3618        | 3.7767 | 20500 | 1.3461          |
| 0.3856        | 3.8688 | 21000 | 1.3461          |
| 0.3586        | 3.9609 | 21500 | 1.3460          |


### Framework versions

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