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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: lens-2 |
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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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# lens-2 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5324 |
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- Accuracy: 0.545 |
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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: 1e-05 |
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- train_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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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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| 0.0399 | 1.0 | 100 | 2.1707 | 0.52 | |
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| 0.069 | 2.0 | 200 | 2.2835 | 0.52 | |
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| 0.0631 | 3.0 | 300 | 2.5655 | 0.5 | |
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| 0.0667 | 4.0 | 400 | 2.1765 | 0.55 | |
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| 0.0055 | 5.0 | 500 | 2.4217 | 0.535 | |
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| 0.0087 | 6.0 | 600 | 2.3678 | 0.545 | |
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| 0.0492 | 7.0 | 700 | 2.4301 | 0.535 | |
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| 0.0049 | 8.0 | 800 | 2.3669 | 0.545 | |
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| 0.0091 | 9.0 | 900 | 2.5554 | 0.5 | |
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| 0.016 | 10.0 | 1000 | 2.4330 | 0.545 | |
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| 0.0345 | 11.0 | 1100 | 2.3653 | 0.575 | |
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| 0.1143 | 12.0 | 1200 | 2.5124 | 0.54 | |
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| 0.2871 | 13.0 | 1300 | 2.3495 | 0.555 | |
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| 0.1154 | 14.0 | 1400 | 2.2519 | 0.56 | |
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| 0.1388 | 15.0 | 1500 | 2.4013 | 0.54 | |
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| 0.1445 | 16.0 | 1600 | 2.3764 | 0.535 | |
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| 0.1094 | 17.0 | 1700 | 2.5227 | 0.5 | |
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| 0.0884 | 18.0 | 1800 | 2.4164 | 0.55 | |
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| 0.156 | 19.0 | 1900 | 2.4202 | 0.555 | |
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| 0.0055 | 20.0 | 2000 | 2.5324 | 0.545 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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