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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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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: emotion_model |
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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: 0.6 |
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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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# emotion_model |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3497 |
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- Accuracy: 0.6 |
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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: 0.0001 |
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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: 50 |
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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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| 2.0823 | 1.0 | 10 | 2.0560 | 0.1625 | |
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| 2.0479 | 2.0 | 20 | 2.0218 | 0.2812 | |
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| 1.9636 | 3.0 | 30 | 1.8882 | 0.4062 | |
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| 1.7902 | 4.0 | 40 | 1.6881 | 0.4313 | |
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| 1.5792 | 5.0 | 50 | 1.6159 | 0.3688 | |
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| 1.4429 | 6.0 | 60 | 1.3871 | 0.5687 | |
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| 1.2854 | 7.0 | 70 | 1.2973 | 0.5437 | |
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| 1.1487 | 8.0 | 80 | 1.2303 | 0.6 | |
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| 1.0374 | 9.0 | 90 | 1.2661 | 0.5375 | |
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| 0.9584 | 10.0 | 100 | 1.1662 | 0.5563 | |
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| 0.8108 | 11.0 | 110 | 1.2135 | 0.5312 | |
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| 0.7402 | 12.0 | 120 | 1.2117 | 0.5813 | |
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| 0.6349 | 13.0 | 130 | 1.1176 | 0.6062 | |
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| 0.5674 | 14.0 | 140 | 1.1794 | 0.575 | |
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| 0.5103 | 15.0 | 150 | 1.0948 | 0.6375 | |
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| 0.4826 | 16.0 | 160 | 1.1833 | 0.5875 | |
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| 0.4128 | 17.0 | 170 | 1.2601 | 0.5375 | |
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| 0.3664 | 18.0 | 180 | 1.3378 | 0.55 | |
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| 0.3112 | 19.0 | 190 | 1.2789 | 0.5437 | |
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| 0.335 | 20.0 | 200 | 1.2913 | 0.5625 | |
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| 0.3261 | 21.0 | 210 | 1.1114 | 0.6 | |
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| 0.3443 | 22.0 | 220 | 1.2177 | 0.5938 | |
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| 0.2642 | 23.0 | 230 | 1.2299 | 0.5938 | |
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| 0.2895 | 24.0 | 240 | 1.2339 | 0.5813 | |
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| 0.266 | 25.0 | 250 | 1.2384 | 0.5875 | |
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| 0.2725 | 26.0 | 260 | 1.2100 | 0.6062 | |
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| 0.2725 | 27.0 | 270 | 1.3073 | 0.575 | |
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| 0.2637 | 28.0 | 280 | 1.3019 | 0.5875 | |
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| 0.2561 | 29.0 | 290 | 1.3597 | 0.5437 | |
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| 0.2375 | 30.0 | 300 | 1.3404 | 0.5563 | |
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| 0.2188 | 31.0 | 310 | 1.2922 | 0.5813 | |
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| 0.2141 | 32.0 | 320 | 1.3778 | 0.5312 | |
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| 0.198 | 33.0 | 330 | 1.3473 | 0.5875 | |
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| 0.1805 | 34.0 | 340 | 1.3984 | 0.5437 | |
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| 0.1888 | 35.0 | 350 | 1.3508 | 0.5813 | |
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| 0.1867 | 36.0 | 360 | 1.3531 | 0.575 | |
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| 0.1596 | 37.0 | 370 | 1.5846 | 0.4875 | |
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| 0.1564 | 38.0 | 380 | 1.3380 | 0.5687 | |
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| 0.1719 | 39.0 | 390 | 1.5206 | 0.5312 | |
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| 0.1678 | 40.0 | 400 | 1.2929 | 0.5875 | |
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| 0.136 | 41.0 | 410 | 1.5031 | 0.55 | |
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| 0.1602 | 42.0 | 420 | 1.3855 | 0.5625 | |
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| 0.174 | 43.0 | 430 | 1.4385 | 0.5875 | |
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| 0.179 | 44.0 | 440 | 1.3153 | 0.575 | |
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| 0.1284 | 45.0 | 450 | 1.4295 | 0.5875 | |
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| 0.1419 | 46.0 | 460 | 1.4126 | 0.575 | |
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| 0.1425 | 47.0 | 470 | 1.3760 | 0.5687 | |
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| 0.1602 | 48.0 | 480 | 1.4374 | 0.5875 | |
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| 0.1473 | 49.0 | 490 | 1.3126 | 0.5813 | |
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| 0.153 | 50.0 | 500 | 1.3497 | 0.6 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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