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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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- image_folder |
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metrics: |
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- accuracy |
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- precision |
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- f1 |
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model-index: |
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- name: emotion_classification |
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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: image_folder |
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type: image_folder |
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config: FastJobs--Visual_Emotional_Analysis |
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split: train |
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args: FastJobs--Visual_Emotional_Analysis |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.64375 |
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- name: Precision |
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type: precision |
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value: 0.6639732142857142 |
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- name: F1 |
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type: f1 |
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value: 0.640682001352849 |
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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_classification |
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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 image_folder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0750 |
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- Accuracy: 0.6438 |
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- Precision: 0.6640 |
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- F1: 0.6407 |
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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: 64 |
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- eval_batch_size: 64 |
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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: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
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| 2.0755 | 1.0 | 10 | 2.0787 | 0.1437 | 0.1529 | 0.1414 | |
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| 2.0711 | 2.0 | 20 | 2.0698 | 0.1875 | 0.1926 | 0.1832 | |
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| 2.0533 | 3.0 | 30 | 2.0520 | 0.2 | 0.2127 | 0.1961 | |
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| 2.0225 | 4.0 | 40 | 2.0173 | 0.225 | 0.2228 | 0.2054 | |
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| 1.9569 | 5.0 | 50 | 1.9289 | 0.2812 | 0.3345 | 0.2544 | |
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| 1.8501 | 6.0 | 60 | 1.7792 | 0.3688 | 0.4904 | 0.3225 | |
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| 1.7072 | 7.0 | 70 | 1.6236 | 0.4313 | 0.4131 | 0.3883 | |
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| 1.6065 | 8.0 | 80 | 1.5276 | 0.45 | 0.4533 | 0.3920 | |
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| 1.539 | 9.0 | 90 | 1.4747 | 0.4938 | 0.4748 | 0.4563 | |
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| 1.5086 | 10.0 | 100 | 1.4393 | 0.4938 | 0.4557 | 0.4466 | |
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| 1.4479 | 11.0 | 110 | 1.3893 | 0.5188 | 0.4563 | 0.4696 | |
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| 1.3683 | 12.0 | 120 | 1.3534 | 0.5437 | 0.5081 | 0.5149 | |
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| 1.3288 | 13.0 | 130 | 1.3392 | 0.5563 | 0.5569 | 0.5323 | |
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| 1.2514 | 14.0 | 140 | 1.2723 | 0.5625 | 0.5467 | 0.5246 | |
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| 1.2116 | 15.0 | 150 | 1.2526 | 0.5875 | 0.5554 | 0.5601 | |
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| 1.1824 | 16.0 | 160 | 1.2047 | 0.5938 | 0.6100 | 0.5697 | |
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| 1.1323 | 17.0 | 170 | 1.1950 | 0.5813 | 0.5331 | 0.5472 | |
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| 1.0782 | 18.0 | 180 | 1.1802 | 0.5875 | 0.5911 | 0.5807 | |
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| 1.0304 | 19.0 | 190 | 1.1534 | 0.6125 | 0.6133 | 0.6012 | |
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| 0.982 | 20.0 | 200 | 1.1302 | 0.6 | 0.5923 | 0.5806 | |
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| 0.9309 | 21.0 | 210 | 1.1849 | 0.5938 | 0.6157 | 0.5723 | |
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| 0.9205 | 22.0 | 220 | 1.1483 | 0.6 | 0.6137 | 0.5882 | |
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| 0.8275 | 23.0 | 230 | 1.1332 | 0.5938 | 0.6192 | 0.5894 | |
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| 0.8472 | 24.0 | 240 | 1.1195 | 0.625 | 0.6444 | 0.6242 | |
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| 0.7974 | 25.0 | 250 | 1.1444 | 0.6062 | 0.6277 | 0.6035 | |
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| 0.7532 | 26.0 | 260 | 1.1312 | 0.5875 | 0.6036 | 0.5832 | |
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| 0.7596 | 27.0 | 270 | 1.1217 | 0.6062 | 0.6412 | 0.6098 | |
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| 0.6818 | 28.0 | 280 | 1.1736 | 0.5625 | 0.6180 | 0.5473 | |
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| 0.6484 | 29.0 | 290 | 1.1630 | 0.5563 | 0.5887 | 0.5367 | |
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| 0.6578 | 30.0 | 300 | 1.0750 | 0.6438 | 0.6640 | 0.6407 | |
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| 0.6235 | 31.0 | 310 | 1.0676 | 0.6438 | 0.6556 | 0.6422 | |
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| 0.5966 | 32.0 | 320 | 1.0531 | 0.6438 | 0.6421 | 0.6385 | |
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| 0.5819 | 33.0 | 330 | 1.1244 | 0.6188 | 0.6315 | 0.6176 | |
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| 0.5585 | 34.0 | 340 | 1.1466 | 0.5813 | 0.6136 | 0.5790 | |
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| 0.5696 | 35.0 | 350 | 1.0703 | 0.6438 | 0.6614 | 0.6481 | |
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| 0.5476 | 36.0 | 360 | 1.1136 | 0.6438 | 0.6764 | 0.6466 | |
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| 0.475 | 37.0 | 370 | 1.1122 | 0.6375 | 0.6612 | 0.6340 | |
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| 0.5381 | 38.0 | 380 | 1.1547 | 0.6188 | 0.6570 | 0.6122 | |
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| 0.5161 | 39.0 | 390 | 1.2268 | 0.5875 | 0.6161 | 0.5704 | |
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| 0.4528 | 40.0 | 400 | 1.1065 | 0.6188 | 0.6314 | 0.6122 | |
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| 0.401 | 41.0 | 410 | 1.1209 | 0.6438 | 0.6550 | 0.6440 | |
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| 0.4067 | 42.0 | 420 | 1.1440 | 0.6312 | 0.6345 | 0.6251 | |
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| 0.3831 | 43.0 | 430 | 1.1972 | 0.6188 | 0.6480 | 0.6075 | |
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| 0.4073 | 44.0 | 440 | 1.2422 | 0.6062 | 0.6644 | 0.6028 | |
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| 0.371 | 45.0 | 450 | 1.2152 | 0.5875 | 0.6087 | 0.5848 | |
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| 0.396 | 46.0 | 460 | 1.1972 | 0.6125 | 0.6306 | 0.6106 | |
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| 0.3322 | 47.0 | 470 | 1.2979 | 0.5813 | 0.6158 | 0.5811 | |
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| 0.3691 | 48.0 | 480 | 1.1657 | 0.625 | 0.6371 | 0.6162 | |
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| 0.3219 | 49.0 | 490 | 1.1786 | 0.6 | 0.6417 | 0.5997 | |
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| 0.3371 | 50.0 | 500 | 1.2126 | 0.6188 | 0.6396 | 0.6149 | |
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| 0.3781 | 51.0 | 510 | 1.2246 | 0.6 | 0.6244 | 0.5972 | |
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| 0.3629 | 52.0 | 520 | 1.1820 | 0.6188 | 0.6437 | 0.6122 | |
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| 0.3025 | 53.0 | 530 | 1.1795 | 0.6062 | 0.6326 | 0.6063 | |
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| 0.309 | 54.0 | 540 | 1.1647 | 0.625 | 0.6510 | 0.6252 | |
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| 0.2999 | 55.0 | 550 | 1.2023 | 0.6375 | 0.6449 | 0.6373 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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