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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: celebrity-classifier |
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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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# celebrity-classifier |
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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: 0.9089 |
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- Accuracy: 0.7982 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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| 0.2075 | 1.0 | 227 | 1.0255 | 0.7831 | |
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| 0.1359 | 2.0 | 455 | 1.1713 | 0.7517 | |
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| 0.1703 | 3.0 | 682 | 1.1582 | 0.7503 | |
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| 0.1052 | 4.0 | 910 | 1.1482 | 0.7567 | |
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| 0.0826 | 5.0 | 1137 | 1.1340 | 0.7514 | |
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| 0.1412 | 6.0 | 1365 | 1.1149 | 0.7514 | |
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| 0.105 | 7.0 | 1592 | 1.1071 | 0.7523 | |
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| 0.1067 | 8.0 | 1820 | 1.1161 | 0.7539 | |
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| 0.1329 | 9.0 | 2047 | 1.0587 | 0.7693 | |
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| 0.1196 | 10.0 | 2275 | 1.0416 | 0.7688 | |
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| 0.1368 | 11.0 | 2502 | 1.0618 | 0.7663 | |
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| 0.1162 | 12.0 | 2730 | 1.0285 | 0.7721 | |
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| 0.145 | 13.0 | 2957 | 1.0040 | 0.7776 | |
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| 0.1449 | 14.0 | 3185 | 0.9967 | 0.7800 | |
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| 0.1135 | 15.0 | 3412 | 0.9603 | 0.7842 | |
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| 0.1266 | 16.0 | 3640 | 0.9333 | 0.7861 | |
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| 0.1571 | 17.0 | 3867 | 0.9643 | 0.7836 | |
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| 0.278 | 18.0 | 4095 | 0.9526 | 0.7861 | |
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| 0.2596 | 19.0 | 4322 | 0.9022 | 0.7965 | |
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| 0.2432 | 19.96 | 4540 | 0.9089 | 0.7982 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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