metadata
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
model-index:
- name: clip-finetuned-csu-p14-336-e3l57-l
results: []
clip-finetuned-csu-p14-336-e3l57-l
This model is a fine-tuned version of openai/clip-vit-large-patch14-336 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2831
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-07
- train_batch_size: 256
- 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 |
---|---|---|---|
0.3448 | 0.0921 | 500 | 1.0839 |
0.2708 | 0.1842 | 1000 | 0.8948 |
0.177 | 0.2763 | 1500 | 0.8396 |
0.1831 | 0.3685 | 2000 | 0.7721 |
0.2038 | 0.4606 | 2500 | 0.7446 |
0.1309 | 0.5527 | 3000 | 0.7235 |
0.1431 | 0.6448 | 3500 | 0.6691 |
0.1411 | 0.7369 | 4000 | 0.6437 |
0.0849 | 0.8290 | 4500 | 0.4805 |
0.1026 | 0.9211 | 5000 | 0.4800 |
0.1201 | 1.0133 | 5500 | 0.4810 |
0.0757 | 1.1054 | 6000 | 0.4692 |
0.0696 | 1.1975 | 6500 | 0.4764 |
0.0911 | 1.2896 | 7000 | 0.4601 |
0.0806 | 1.3817 | 7500 | 0.4590 |
0.088 | 1.4738 | 8000 | 0.4654 |
0.0878 | 1.5660 | 8500 | 0.4769 |
0.0369 | 1.6581 | 9000 | 0.4684 |
0.1034 | 1.7502 | 9500 | 0.4716 |
0.0852 | 1.8423 | 10000 | 0.4720 |
0.0493 | 1.9344 | 10500 | 0.4714 |
0.0603 | 2.0265 | 11000 | 0.4661 |
0.0547 | 2.1186 | 11500 | 0.4669 |
0.0793 | 2.2108 | 12000 | 0.4664 |
0.0415 | 2.3024 | 12500 | 0.2888 |
0.0565 | 2.3945 | 13000 | 0.2910 |
0.0629 | 2.4866 | 13500 | 0.2889 |
0.0584 | 2.5787 | 14000 | 0.2874 |
0.0582 | 2.6708 | 14500 | 0.2863 |
0.052 | 2.7629 | 15000 | 0.2846 |
0.0402 | 2.8550 | 15500 | 0.2835 |
0.0518 | 2.9471 | 16000 | 0.2831 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 1.12.1
- Datasets 2.21.0
- Tokenizers 0.19.1