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jalaneunos
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vit-base-patch16-224-in21k-finetuned-FER2013

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  1. README.md +17 -17
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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8683385579937304
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.3321
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- - Accuracy: 0.8683
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.495 | 1.0 | 202 | 0.4660 | 0.7739 |
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- | 0.4632 | 2.0 | 404 | 0.3820 | 0.8286 |
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- | 0.4013 | 3.0 | 606 | 0.3562 | 0.8447 |
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- | 0.3883 | 4.0 | 808 | 0.3426 | 0.8516 |
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- | 0.3801 | 5.0 | 1010 | 0.3303 | 0.8561 |
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- | 0.3612 | 6.0 | 1212 | 0.3362 | 0.8558 |
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- | 0.3504 | 7.0 | 1414 | 0.3302 | 0.8652 |
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- | 0.3366 | 8.0 | 1616 | 0.3321 | 0.8683 |
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- | 0.3007 | 9.0 | 1818 | 0.3330 | 0.8666 |
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- | 0.3089 | 10.0 | 2020 | 0.3327 | 0.8656 |
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  ### Framework versions
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- - Transformers 4.37.0
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- - Pytorch 2.1.0+cu121
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- - Datasets 2.16.1
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- - Tokenizers 0.15.0
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8732149076976663
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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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  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: 0.3264
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+ - Accuracy: 0.8732
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4811 | 1.0 | 202 | 0.4315 | 0.8004 |
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+ | 0.4287 | 2.0 | 404 | 0.3579 | 0.8433 |
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+ | 0.4184 | 3.0 | 606 | 0.3517 | 0.8467 |
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+ | 0.3931 | 4.0 | 808 | 0.3308 | 0.8555 |
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+ | 0.3667 | 5.0 | 1010 | 0.3204 | 0.8610 |
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+ | 0.3545 | 6.0 | 1212 | 0.3144 | 0.8659 |
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+ | 0.3137 | 7.0 | 1414 | 0.3308 | 0.8642 |
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+ | 0.3178 | 8.0 | 1616 | 0.3230 | 0.8645 |
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+ | 0.2998 | 9.0 | 1818 | 0.3206 | 0.8708 |
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+ | 0.2773 | 10.0 | 2020 | 0.3264 | 0.8732 |
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  ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2