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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-e4l59-l |
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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-finetuned-csu-p14-336-e4l59-l |
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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: 1.3460 |
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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-09 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.3952 | 0.0921 | 500 | 1.4940 | |
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| 0.4562 | 0.1842 | 1000 | 1.4853 | |
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| 0.5131 | 0.2763 | 1500 | 1.4758 | |
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| 0.4481 | 0.3685 | 2000 | 1.4676 | |
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| 0.4839 | 0.4606 | 2500 | 1.4585 | |
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| 0.4377 | 0.5527 | 3000 | 1.4508 | |
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| 0.4231 | 0.6448 | 3500 | 1.4432 | |
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| 0.4369 | 0.7369 | 4000 | 1.4366 | |
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| 0.4082 | 0.8290 | 4500 | 1.4302 | |
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| 0.4234 | 0.9211 | 5000 | 1.4243 | |
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| 0.4266 | 1.0133 | 5500 | 1.4191 | |
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| 0.4438 | 1.1054 | 6000 | 1.4137 | |
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| 0.3814 | 1.1975 | 6500 | 1.4085 | |
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| 0.3327 | 1.2896 | 7000 | 1.4042 | |
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| 0.4045 | 1.3817 | 7500 | 1.3989 | |
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| 0.4038 | 1.4738 | 8000 | 1.3937 | |
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| 0.3659 | 1.5660 | 8500 | 1.3894 | |
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| 0.4282 | 1.6581 | 9000 | 1.3855 | |
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| 0.4173 | 1.7502 | 9500 | 1.3816 | |
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| 0.3758 | 1.8423 | 10000 | 1.3779 | |
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| 0.4105 | 1.9344 | 10500 | 1.3745 | |
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| 0.3765 | 2.0265 | 11000 | 1.3716 | |
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| 0.3746 | 2.1186 | 11500 | 1.3690 | |
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| 0.3783 | 2.2108 | 12000 | 1.3662 | |
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| 0.3832 | 2.3029 | 12500 | 1.3640 | |
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| 0.3984 | 2.3950 | 13000 | 1.3617 | |
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| 0.4124 | 2.4871 | 13500 | 1.3593 | |
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| 0.3363 | 2.5792 | 14000 | 1.3572 | |
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| 0.3274 | 2.6713 | 14500 | 1.3555 | |
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| 0.4039 | 2.7634 | 15000 | 1.3538 | |
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| 0.378 | 2.8556 | 15500 | 1.3524 | |
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| 0.3543 | 2.9477 | 16000 | 1.3511 | |
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| 0.3606 | 3.0398 | 16500 | 1.3501 | |
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| 0.4024 | 3.1319 | 17000 | 1.3491 | |
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| 0.3182 | 3.2240 | 17500 | 1.3482 | |
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| 0.3564 | 3.3161 | 18000 | 1.3475 | |
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| 0.3842 | 3.4083 | 18500 | 1.3470 | |
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| 0.352 | 3.5004 | 19000 | 1.3467 | |
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| 0.3828 | 3.5925 | 19500 | 1.3464 | |
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| 0.39 | 3.6846 | 20000 | 1.3462 | |
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| 0.3618 | 3.7767 | 20500 | 1.3461 | |
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| 0.3856 | 3.8688 | 21000 | 1.3461 | |
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| 0.3586 | 3.9609 | 21500 | 1.3460 | |
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### Framework versions |
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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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