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README.md
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---
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library_name: transformers
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base_model: openai/clip-vit-base-patch32
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-mnist
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-mnist
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This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0201
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- Accuracy: 0.9937
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.4813 | 1.0 | 422 | 0.1699 | 0.9447 |
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| 0.4611 | 2.0 | 844 | 0.0592 | 0.9818 |
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| 0.4193 | 3.0 | 1266 | 0.0584 | 0.9822 |
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| 0.3782 | 4.0 | 1688 | 0.0669 | 0.9788 |
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| 0.3293 | 5.0 | 2110 | 0.0349 | 0.9887 |
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| 0.3383 | 6.0 | 2532 | 0.0349 | 0.9888 |
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| 0.3291 | 7.0 | 2954 | 0.0381 | 0.9873 |
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| 0.2783 | 8.0 | 3376 | 0.0225 | 0.9932 |
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| 0.2631 | 9.0 | 3798 | 0.0217 | 0.9933 |
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| 0.2815 | 10.0 | 4220 | 0.0201 | 0.9937 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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