---
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: 0.8656

## 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-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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.3758        | 0.0921 | 500   | 1.4185          |
| 0.4103        | 0.1842 | 1000  | 1.3501          |
| 0.433         | 0.2763 | 1500  | 1.2885          |
| 0.3424        | 0.3685 | 2000  | 1.2391          |
| 0.3645        | 0.4606 | 2500  | 1.1902          |
| 0.3172        | 0.5527 | 3000  | 1.1506          |
| 0.2751        | 0.6448 | 3500  | 1.1169          |
| 0.2919        | 0.7369 | 4000  | 1.0921          |
| 0.2583        | 0.8290 | 4500  | 1.0721          |
| 0.2679        | 0.9211 | 5000  | 1.0519          |
| 0.2472        | 1.0133 | 5500  | 1.0356          |
| 0.26          | 1.1054 | 6000  | 1.0177          |
| 0.2153        | 1.1975 | 6500  | 1.0045          |
| 0.1791        | 1.2896 | 7000  | 0.9927          |
| 0.2082        | 1.3817 | 7500  | 0.9804          |
| 0.196         | 1.4738 | 8000  | 0.9712          |
| 0.1946        | 1.5660 | 8500  | 0.9621          |
| 0.2422        | 1.6581 | 9000  | 0.9537          |
| 0.2106        | 1.7502 | 9500  | 0.9458          |
| 0.1801        | 1.8423 | 10000 | 0.9393          |
| 0.2117        | 1.9344 | 10500 | 0.9308          |
| 0.2061        | 2.0265 | 11000 | 0.9237          |
| 0.1878        | 2.1186 | 11500 | 0.9167          |
| 0.1655        | 2.2108 | 12000 | 0.9109          |
| 0.1946        | 2.3029 | 12500 | 0.9071          |
| 0.1882        | 2.3950 | 13000 | 0.9021          |
| 0.1871        | 2.4871 | 13500 | 0.8960          |
| 0.1419        | 2.5792 | 14000 | 0.8913          |
| 0.1431        | 2.6713 | 14500 | 0.8879          |
| 0.1811        | 2.7634 | 15000 | 0.8848          |
| 0.1694        | 2.8556 | 15500 | 0.8827          |
| 0.1718        | 2.9477 | 16000 | 0.8798          |
| 0.153         | 3.0398 | 16500 | 0.8777          |
| 0.1715        | 3.1319 | 17000 | 0.8759          |
| 0.1558        | 3.2240 | 17500 | 0.8742          |
| 0.1384        | 3.3161 | 18000 | 0.8715          |
| 0.1788        | 3.4083 | 18500 | 0.8695          |
| 0.1668        | 3.5004 | 19000 | 0.8685          |
| 0.1697        | 3.5925 | 19500 | 0.8674          |
| 0.1764        | 3.6846 | 20000 | 0.8666          |
| 0.1417        | 3.7767 | 20500 | 0.8660          |
| 0.1556        | 3.8688 | 21000 | 0.8657          |
| 0.1605        | 3.9609 | 21500 | 0.8656          |


### Framework versions

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