metadata
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
model-index:
- name: clip-finetuned-csu-p14-336-e3l56-l
results: []
clip-finetuned-csu-p14-336-e3l56-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: 0.6863
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-06
- 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 |
---|---|---|---|
0.2253 | 0.0921 | 500 | 1.4694 |
0.2544 | 0.1842 | 1000 | 1.5421 |
0.3236 | 0.2763 | 1500 | 1.4643 |
0.1888 | 0.3685 | 2000 | 1.3194 |
0.2563 | 0.4606 | 2500 | 1.3764 |
0.2794 | 0.5527 | 3000 | 1.3007 |
0.1749 | 0.6448 | 3500 | 1.3361 |
0.2672 | 0.7369 | 4000 | 1.2684 |
0.218 | 0.8290 | 4500 | 1.1065 |
0.1665 | 0.9211 | 5000 | 1.0620 |
0.1842 | 1.0133 | 5500 | 0.9443 |
0.1183 | 1.1054 | 6000 | 0.9431 |
0.1066 | 1.1975 | 6500 | 1.0051 |
0.0901 | 1.2896 | 7000 | 1.0017 |
0.112 | 1.3817 | 7500 | 1.0030 |
0.1265 | 1.4738 | 8000 | 0.9463 |
0.1193 | 1.5660 | 8500 | 1.0378 |
0.1318 | 1.6581 | 9000 | 0.9299 |
0.1262 | 1.7502 | 9500 | 0.9714 |
0.101 | 1.8423 | 10000 | 0.8754 |
0.1158 | 1.9344 | 10500 | 0.8075 |
0.0656 | 2.0265 | 11000 | 0.8281 |
0.0854 | 2.1186 | 11500 | 0.7756 |
0.0574 | 2.2108 | 12000 | 0.7431 |
0.0643 | 2.3029 | 12500 | 0.7556 |
0.0657 | 2.3950 | 13000 | 0.7819 |
0.0372 | 2.4871 | 13500 | 0.7689 |
0.0286 | 2.5792 | 14000 | 0.7623 |
0.0581 | 2.6713 | 14500 | 0.7251 |
0.0578 | 2.7634 | 15000 | 0.6913 |
0.0442 | 2.8556 | 15500 | 0.6863 |
0.0304 | 2.9477 | 16000 | 0.6906 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 1.12.1
- Datasets 2.21.0
- Tokenizers 0.19.1