| --- |
| library_name: transformers |
| base_model: openai/clip-vit-large-patch14 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: clip-vit-large-patch14-finetuned-openai-clip-vit-large-patch14-mnist |
| 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-vit-large-patch14-finetuned-openai-clip-vit-large-patch14-mnist |
|
|
| This model is a fine-tuned version of [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0258 |
| - Accuracy: 0.9925 |
|
|
| ## 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-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.5191 | 1.0 | 422 | 0.0737 | 0.9802 | |
| | 0.4218 | 2.0 | 844 | 0.0505 | 0.9845 | |
| | 0.3987 | 3.0 | 1266 | 0.0497 | 0.9853 | |
| | 0.3776 | 4.0 | 1688 | 0.0466 | 0.985 | |
| | 0.3244 | 5.0 | 2110 | 0.0366 | 0.9897 | |
| | 0.3269 | 6.0 | 2532 | 0.0491 | 0.9867 | |
| | 0.3072 | 7.0 | 2954 | 0.0375 | 0.9885 | |
| | 0.2343 | 8.0 | 3376 | 0.0339 | 0.9908 | |
| | 0.2395 | 9.0 | 3798 | 0.0274 | 0.9912 | |
| | 0.222 | 10.0 | 4220 | 0.0258 | 0.9925 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
