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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: openai/clip-vit-large-patch14-336
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: clip-finetuned-csu-p14-336-e4l57-l
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+ results: []
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+ ---
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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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+
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+ # clip-finetuned-csu-p14-336-e4l57-l
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4956
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-07
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+ - train_batch_size: 128
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+ - num_epochs: 4.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:-----:|:---------------:|
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+ | 0.271 | 0.0921 | 500 | 1.0693 |
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+ | 0.2493 | 0.1842 | 1000 | 0.9427 |
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+ | 0.2348 | 0.2763 | 1500 | 0.8727 |
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+ | 0.1552 | 0.3685 | 2000 | 0.8326 |
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+ | 0.1753 | 0.4606 | 2500 | 0.7550 |
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+ | 0.1659 | 0.5527 | 3000 | 0.7192 |
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+ | 0.105 | 0.6448 | 3500 | 0.7118 |
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+ | 0.1336 | 0.7369 | 4000 | 0.6953 |
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+ | 0.1154 | 0.8290 | 4500 | 0.6745 |
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+ | 0.108 | 0.9211 | 5000 | 0.6560 |
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+ | 0.1106 | 1.0133 | 5500 | 0.6367 |
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+ | 0.0591 | 1.1054 | 6000 | 0.6259 |
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+ | 0.0745 | 1.1975 | 6500 | 0.6210 |
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+ | 0.0502 | 1.2896 | 7000 | 0.6133 |
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+ | 0.079 | 1.3817 | 7500 | 0.6007 |
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+ | 0.0776 | 1.4738 | 8000 | 0.5866 |
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+ | 0.0492 | 1.5660 | 8500 | 0.5679 |
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+ | 0.0794 | 1.6581 | 9000 | 0.5762 |
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+ | 0.0677 | 1.7502 | 9500 | 0.5566 |
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+ | 0.0566 | 1.8423 | 10000 | 0.5482 |
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+ | 0.0828 | 1.9344 | 10500 | 0.5500 |
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+ | 0.0573 | 2.0265 | 11000 | 0.5342 |
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+ | 0.0401 | 2.1186 | 11500 | 0.5351 |
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+ | 0.0152 | 2.2108 | 12000 | 0.5349 |
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+ | 0.0638 | 2.3029 | 12500 | 0.5318 |
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+ | 0.0488 | 2.3950 | 13000 | 0.5306 |
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+ | 0.0456 | 2.4871 | 13500 | 0.5211 |
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+ | 0.0264 | 2.5792 | 14000 | 0.5194 |
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+ | 0.0381 | 2.6713 | 14500 | 0.5206 |
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+ | 0.0413 | 2.7634 | 15000 | 0.5168 |
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+ | 0.0392 | 2.8556 | 15500 | 0.5149 |
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+ | 0.0352 | 2.9477 | 16000 | 0.5112 |
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+ | 0.0467 | 3.0398 | 16500 | 0.5098 |
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+ | 0.0366 | 3.1319 | 17000 | 0.5089 |
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+ | 0.0454 | 3.2240 | 17500 | 0.5104 |
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+ | 0.0209 | 3.3161 | 18000 | 0.5071 |
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+ | 0.0636 | 3.4083 | 18500 | 0.5045 |
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+ | 0.0159 | 3.5004 | 19000 | 0.5019 |
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+ | 0.0303 | 3.5925 | 19500 | 0.4985 |
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+ | 0.0353 | 3.6846 | 20000 | 0.4975 |
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+ | 0.0261 | 3.7767 | 20500 | 0.4962 |
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+ | 0.0291 | 3.8688 | 21000 | 0.4956 |
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+ | 0.0338 | 3.9609 | 21500 | 0.4956 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.0.dev0
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+ - Pytorch 1.12.1
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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