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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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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: exper2_mesum5 |
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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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# exper2_mesum5 |
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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 the sudo-s/herbier_mesuem5 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4589 |
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- Accuracy: 0.1308 |
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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: 0.002 |
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- train_batch_size: 16 |
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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 |
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- mixed_precision_training: Native AMP |
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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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| 4.4265 | 0.23 | 100 | 4.3676 | 0.0296 | |
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| 4.1144 | 0.47 | 200 | 4.1606 | 0.0544 | |
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| 4.0912 | 0.7 | 300 | 4.1071 | 0.0509 | |
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| 4.0361 | 0.93 | 400 | 4.0625 | 0.0669 | |
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| 4.0257 | 1.16 | 500 | 3.9682 | 0.0822 | |
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| 3.8846 | 1.4 | 600 | 3.9311 | 0.0834 | |
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| 3.9504 | 1.63 | 700 | 3.9255 | 0.0698 | |
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| 3.9884 | 1.86 | 800 | 3.9404 | 0.0722 | |
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| 3.7191 | 2.09 | 900 | 3.8262 | 0.0935 | |
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| 3.7952 | 2.33 | 1000 | 3.8236 | 0.0734 | |
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| 3.8085 | 2.56 | 1100 | 3.7694 | 0.0964 | |
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| 3.7535 | 2.79 | 1200 | 3.6757 | 0.1059 | |
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| 3.4218 | 3.02 | 1300 | 3.6474 | 0.1095 | |
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| 3.5172 | 3.26 | 1400 | 3.5621 | 0.1166 | |
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| 3.5173 | 3.49 | 1500 | 3.5579 | 0.1207 | |
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| 3.4346 | 3.72 | 1600 | 3.4817 | 0.1249 | |
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| 3.3995 | 3.95 | 1700 | 3.4589 | 0.1308 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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