|
--- |
|
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: 1.9056 |
|
|
|
## 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: 8.810707926567202e-07 |
|
- 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 | |
|
|:-------------:|:------:|:-----:|:---------------:| |
|
| 0.7336 | 0.0921 | 500 | 2.0781 | |
|
| 0.6953 | 0.1842 | 1000 | 2.0783 | |
|
| 0.6953 | 0.2763 | 1500 | 2.0777 | |
|
| 0.6932 | 0.3684 | 2000 | 2.0722 | |
|
| 0.6907 | 0.4605 | 2500 | 2.0792 | |
|
| 0.7043 | 0.5526 | 3000 | 2.0205 | |
|
| 0.7078 | 0.6447 | 3500 | 2.1256 | |
|
| 0.7034 | 0.7368 | 4000 | 2.0000 | |
|
| 0.6671 | 0.8289 | 4500 | 2.1608 | |
|
| 0.6899 | 0.9210 | 5000 | 2.0940 | |
|
| 0.6649 | 1.0131 | 5500 | 1.9776 | |
|
| 0.6748 | 1.1052 | 6000 | 1.9852 | |
|
| 0.6456 | 1.1973 | 6500 | 1.9981 | |
|
| 0.6514 | 1.2894 | 7000 | 1.9637 | |
|
| 0.6179 | 1.3815 | 7500 | 2.0034 | |
|
| 0.6561 | 1.4736 | 8000 | 2.2865 | |
|
| 0.6328 | 1.5657 | 8500 | 2.4808 | |
|
| 0.7053 | 1.6578 | 9000 | 2.1610 | |
|
| 0.6533 | 1.7499 | 9500 | 1.9845 | |
|
| 0.6594 | 1.8420 | 10000 | 1.9895 | |
|
| 0.6597 | 1.9341 | 10500 | 2.0103 | |
|
| 0.6435 | 2.0262 | 11000 | 2.0589 | |
|
| 0.6404 | 2.1183 | 11500 | 2.0517 | |
|
| 0.6348 | 2.2104 | 12000 | 1.9749 | |
|
| 0.6545 | 2.3024 | 12500 | 1.9681 | |
|
| 0.6323 | 2.3945 | 13000 | 1.9056 | |
|
| 0.6045 | 2.4866 | 13500 | 1.9470 | |
|
| 0.6492 | 2.5787 | 14000 | 2.0177 | |
|
| 0.6512 | 2.6708 | 14500 | 1.9483 | |
|
| 0.6382 | 2.7629 | 15000 | 1.9499 | |
|
| 0.6203 | 2.8550 | 15500 | 1.9529 | |
|
| 0.6241 | 2.9471 | 16000 | 1.9817 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.0.dev0 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|