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---
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
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