metadata
library_name: transformers
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-mnist
results: []
clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-mnist
This model is a fine-tuned version of openai/clip-vit-base-patch32 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0201
- Accuracy: 0.9937
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 |
|---|---|---|---|---|
| 0.4813 | 1.0 | 422 | 0.1699 | 0.9447 |
| 0.4611 | 2.0 | 844 | 0.0592 | 0.9818 |
| 0.4193 | 3.0 | 1266 | 0.0584 | 0.9822 |
| 0.3782 | 4.0 | 1688 | 0.0669 | 0.9788 |
| 0.3293 | 5.0 | 2110 | 0.0349 | 0.9887 |
| 0.3383 | 6.0 | 2532 | 0.0349 | 0.9888 |
| 0.3291 | 7.0 | 2954 | 0.0381 | 0.9873 |
| 0.2783 | 8.0 | 3376 | 0.0225 | 0.9932 |
| 0.2631 | 9.0 | 3798 | 0.0217 | 0.9933 |
| 0.2815 | 10.0 | 4220 | 0.0201 | 0.9937 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1