---
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: 1.9574

## 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-05
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.7076        | 0.0921 | 500   | 2.0787          |
| 0.7045        | 0.1842 | 1000  | 2.0783          |
| 0.7106        | 0.2763 | 1500  | 2.0474          |
| 0.704         | 0.3685 | 2000  | 2.2816          |
| 0.6996        | 0.4606 | 2500  | 2.0450          |
| 0.6739        | 0.5527 | 3000  | 2.0969          |
| 0.6687        | 0.6448 | 3500  | 2.0315          |
| 0.8387        | 0.7369 | 4000  | 2.3810          |
| 0.6988        | 0.8290 | 4500  | 2.0409          |
| 0.6808        | 0.9211 | 5000  | 1.9745          |
| 0.6584        | 1.0133 | 5500  | 1.9649          |
| 0.6567        | 1.1054 | 6000  | 2.0569          |
| 0.6542        | 1.1975 | 6500  | 1.9789          |
| 0.6536        | 1.2896 | 7000  | 1.9676          |
| 0.637         | 1.3817 | 7500  | 2.0040          |
| 0.6409        | 1.4738 | 8000  | 1.9905          |
| 0.6127        | 1.5660 | 8500  | 2.2639          |
| 0.6564        | 1.6581 | 9000  | 1.9574          |
| 0.6813        | 1.7502 | 9500  | 2.0365          |
| 0.6421        | 1.8423 | 10000 | 2.2432          |
| 0.6531        | 1.9344 | 10500 | 1.9985          |
| 0.6388        | 2.0265 | 11000 | 1.9725          |
| 0.6394        | 2.1186 | 11500 | 2.0171          |
| 0.6151        | 2.2108 | 12000 | 1.9587          |
| 0.5947        | 2.3029 | 12500 | 2.0684          |
| 0.6166        | 2.3950 | 13000 | 2.0580          |
| 0.6382        | 2.4871 | 13500 | 2.0209          |
| 0.5949        | 2.5792 | 14000 | 2.0776          |
| 0.6282        | 2.6713 | 14500 | 2.0721          |
| 0.6057        | 2.7634 | 15000 | 2.0813          |
| 0.6229        | 2.8556 | 15500 | 2.0468          |
| 0.612         | 2.9477 | 16000 | 2.0670          |


### Framework versions

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