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--- |
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library_name: transformers |
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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_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: 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: 0.5125 |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3578 |
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- Accuracy: 0.5125 |
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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: 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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| 2.0796 | 1.0 | 10 | 2.0709 | 0.1562 | |
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| 2.0631 | 2.0 | 20 | 2.0496 | 0.225 | |
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| 2.0242 | 3.0 | 30 | 2.0148 | 0.2875 | |
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| 1.9387 | 4.0 | 40 | 1.9268 | 0.325 | |
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| 1.789 | 5.0 | 50 | 1.7454 | 0.3812 | |
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| 1.6216 | 6.0 | 60 | 1.5996 | 0.3937 | |
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| 1.4795 | 7.0 | 70 | 1.5577 | 0.375 | |
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| 1.3735 | 8.0 | 80 | 1.5090 | 0.4062 | |
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| 1.2889 | 9.0 | 90 | 1.4418 | 0.4313 | |
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| 1.2092 | 10.0 | 100 | 1.4209 | 0.425 | |
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| 1.1127 | 11.0 | 110 | 1.3828 | 0.4437 | |
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| 1.032 | 12.0 | 120 | 1.3507 | 0.4562 | |
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| 0.9616 | 13.0 | 130 | 1.3556 | 0.4875 | |
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| 0.9099 | 14.0 | 140 | 1.3204 | 0.5188 | |
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| 0.8425 | 15.0 | 150 | 1.3490 | 0.4688 | |
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| 0.806 | 16.0 | 160 | 1.3690 | 0.5062 | |
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| 0.7377 | 17.0 | 170 | 1.3344 | 0.5563 | |
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| 0.677 | 18.0 | 180 | 1.4178 | 0.4625 | |
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| 0.6071 | 19.0 | 190 | 1.3305 | 0.4875 | |
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| 0.5581 | 20.0 | 200 | 1.3070 | 0.5 | |
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| 0.5599 | 21.0 | 210 | 1.3245 | 0.4938 | |
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| 0.5222 | 22.0 | 220 | 1.3765 | 0.4562 | |
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| 0.4856 | 23.0 | 230 | 1.3345 | 0.5 | |
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| 0.458 | 24.0 | 240 | 1.2938 | 0.5188 | |
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| 0.4393 | 25.0 | 250 | 1.3380 | 0.5062 | |
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| 0.4239 | 26.0 | 260 | 1.3756 | 0.525 | |
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| 0.4443 | 27.0 | 270 | 1.4586 | 0.4813 | |
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| 0.4374 | 28.0 | 280 | 1.2996 | 0.55 | |
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| 0.3917 | 29.0 | 290 | 1.3222 | 0.5062 | |
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| 0.3986 | 30.0 | 300 | 1.4486 | 0.4813 | |
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| 0.353 | 31.0 | 310 | 1.5204 | 0.4562 | |
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| 0.3598 | 32.0 | 320 | 1.3027 | 0.5625 | |
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| 0.3538 | 33.0 | 330 | 1.6122 | 0.4313 | |
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| 0.3246 | 34.0 | 340 | 1.5237 | 0.4437 | |
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| 0.3089 | 35.0 | 350 | 1.4717 | 0.5125 | |
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| 0.3278 | 36.0 | 360 | 1.5666 | 0.45 | |
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| 0.2865 | 37.0 | 370 | 1.4377 | 0.5 | |
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| 0.2958 | 38.0 | 380 | 1.4766 | 0.4938 | |
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| 0.3036 | 39.0 | 390 | 1.5345 | 0.4375 | |
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| 0.286 | 40.0 | 400 | 1.4174 | 0.5062 | |
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| 0.3099 | 41.0 | 410 | 1.4087 | 0.4625 | |
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| 0.2801 | 42.0 | 420 | 1.4439 | 0.4813 | |
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| 0.2973 | 43.0 | 430 | 1.4712 | 0.4938 | |
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| 0.2892 | 44.0 | 440 | 1.4099 | 0.5188 | |
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| 0.2835 | 45.0 | 450 | 1.3011 | 0.5563 | |
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| 0.261 | 46.0 | 460 | 1.6512 | 0.4188 | |
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| 0.2589 | 47.0 | 470 | 1.5651 | 0.4375 | |
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| 0.2806 | 48.0 | 480 | 1.5194 | 0.4938 | |
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| 0.2749 | 49.0 | 490 | 1.4519 | 0.525 | |
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| 0.2482 | 50.0 | 500 | 1.4127 | 0.5188 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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