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--- |
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license: apache-2.0 |
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base_model: Visual-Attention-Network/van-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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- recall |
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- precision |
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model-index: |
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- name: teacher-status-van-tiny-256 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9831460674157303 |
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- name: Recall |
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type: recall |
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value: 0.9789473684210527 |
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- name: Precision |
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type: precision |
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value: 0.9893617021276596 |
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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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# teacher-status-van-tiny-256 |
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This model is a fine-tuned version of [Visual-Attention-Network/van-tiny](https://huggingface.co/Visual-Attention-Network/van-tiny) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0988 |
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- Accuracy: 0.9831 |
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- F1 Score: 0.9841 |
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- Recall: 0.9789 |
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- Precision: 0.9894 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:| |
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| 0.6928 | 0.96 | 12 | 0.6904 | 0.6685 | 0.7631 | 1.0 | 0.6169 | |
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| 0.6893 | 2.0 | 25 | 0.6683 | 0.5393 | 0.6985 | 1.0 | 0.5367 | |
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| 0.6726 | 2.96 | 37 | 0.5704 | 0.5843 | 0.7197 | 1.0 | 0.5621 | |
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| 0.5295 | 4.0 | 50 | 0.4148 | 0.9213 | 0.9263 | 0.9263 | 0.9263 | |
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| 0.4745 | 4.96 | 62 | 0.3108 | 0.9382 | 0.9430 | 0.9579 | 0.9286 | |
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| 0.4206 | 6.0 | 75 | 0.2301 | 0.9438 | 0.9474 | 0.9474 | 0.9474 | |
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| 0.3898 | 6.96 | 87 | 0.1820 | 0.9494 | 0.9519 | 0.9368 | 0.9674 | |
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| 0.3153 | 8.0 | 100 | 0.1545 | 0.9494 | 0.9538 | 0.9789 | 0.93 | |
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| 0.3077 | 8.96 | 112 | 0.1521 | 0.9607 | 0.9622 | 0.9368 | 0.9889 | |
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| 0.3048 | 10.0 | 125 | 0.1331 | 0.9607 | 0.9626 | 0.9474 | 0.9783 | |
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| 0.3004 | 10.96 | 137 | 0.1314 | 0.9607 | 0.9634 | 0.9684 | 0.9583 | |
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| 0.2839 | 12.0 | 150 | 0.1272 | 0.9607 | 0.9622 | 0.9368 | 0.9889 | |
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| 0.286 | 12.96 | 162 | 0.1189 | 0.9607 | 0.9622 | 0.9368 | 0.9889 | |
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| 0.2473 | 14.0 | 175 | 0.0977 | 0.9719 | 0.9733 | 0.9579 | 0.9891 | |
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| 0.2774 | 14.96 | 187 | 0.0988 | 0.9831 | 0.9841 | 0.9789 | 0.9894 | |
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| 0.2541 | 16.0 | 200 | 0.0969 | 0.9719 | 0.9733 | 0.9579 | 0.9891 | |
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| 0.2383 | 16.96 | 212 | 0.1042 | 0.9719 | 0.9733 | 0.9579 | 0.9891 | |
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| 0.2552 | 18.0 | 225 | 0.1081 | 0.9719 | 0.9733 | 0.9579 | 0.9891 | |
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| 0.2223 | 18.96 | 237 | 0.1150 | 0.9663 | 0.9681 | 0.9579 | 0.9785 | |
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| 0.2561 | 20.0 | 250 | 0.1234 | 0.9551 | 0.9574 | 0.9474 | 0.9677 | |
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| 0.2462 | 20.96 | 262 | 0.1178 | 0.9607 | 0.9630 | 0.9579 | 0.9681 | |
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| 0.2294 | 22.0 | 275 | 0.1262 | 0.9382 | 0.9430 | 0.9579 | 0.9286 | |
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| 0.2296 | 22.96 | 287 | 0.1290 | 0.9438 | 0.9479 | 0.9579 | 0.9381 | |
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| 0.2224 | 24.0 | 300 | 0.1153 | 0.9494 | 0.9529 | 0.9579 | 0.9479 | |
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| 0.2205 | 24.96 | 312 | 0.1150 | 0.9494 | 0.9529 | 0.9579 | 0.9479 | |
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| 0.2169 | 26.0 | 325 | 0.1121 | 0.9551 | 0.9574 | 0.9474 | 0.9677 | |
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| 0.2212 | 26.96 | 337 | 0.1145 | 0.9494 | 0.9529 | 0.9579 | 0.9479 | |
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| 0.2188 | 28.0 | 350 | 0.1131 | 0.9494 | 0.9524 | 0.9474 | 0.9574 | |
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| 0.2015 | 28.8 | 360 | 0.1130 | 0.9494 | 0.9524 | 0.9474 | 0.9574 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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