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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-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
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