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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: 13E-affecthq-fer-balanced
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results: []
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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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# 13E-affecthq-fer-balanced
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0526
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- Accuracy: 0.6225
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- Precision: 0.6161
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- Recall: 0.6225
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- F1: 0.6167
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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: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 17
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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: 13
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 1.7863 | 1.0 | 133 | 1.7632 | 0.4005 | 0.3617 | 0.4005 | 0.3058 |
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| 1.3653 | 2.0 | 266 | 1.3630 | 0.5049 | 0.4838 | 0.5049 | 0.4445 |
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| 1.2468 | 3.0 | 399 | 1.2475 | 0.5466 | 0.5451 | 0.5466 | 0.5115 |
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| 1.1527 | 4.0 | 532 | 1.1865 | 0.5761 | 0.5612 | 0.5761 | 0.5580 |
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| 1.0862 | 5.0 | 665 | 1.1448 | 0.5785 | 0.5687 | 0.5785 | 0.5659 |
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| 1.064 | 6.0 | 798 | 1.1108 | 0.5972 | 0.5867 | 0.5972 | 0.5853 |
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| 1.0037 | 7.0 | 931 | 1.0969 | 0.6019 | 0.5968 | 0.6019 | 0.5946 |
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| 0.9533 | 8.0 | 1064 | 1.0764 | 0.6126 | 0.6034 | 0.6126 | 0.6046 |
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| 0.9063 | 9.0 | 1197 | 1.0711 | 0.6155 | 0.6035 | 0.6155 | 0.6047 |
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| 0.8666 | 10.0 | 1330 | 1.0589 | 0.6173 | 0.6107 | 0.6173 | 0.6108 |
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| 0.8364 | 11.0 | 1463 | 1.0556 | 0.6178 | 0.6110 | 0.6178 | 0.6108 |
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| 0.8659 | 12.0 | 1596 | 1.0521 | 0.6197 | 0.6141 | 0.6197 | 0.6151 |
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| 0.8383 | 13.0 | 1729 | 1.0526 | 0.6225 | 0.6161 | 0.6225 | 0.6167 |
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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