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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: finetuned-fer2013-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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# finetuned-fer2013-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: 1.0183
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- Accuracy: 0.6362
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- Precision: 0.6312
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- Recall: 0.6362
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- F1: 0.6310
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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: 16
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- eval_batch_size: 16
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- seed: 17
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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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- num_epochs: 10
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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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| 1.3969 | 1.0 | 267 | 1.3735 | 0.4996 | 0.4776 | 0.4996 | 0.4436 |
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| 1.2341 | 2.0 | 534 | 1.2239 | 0.5442 | 0.5430 | 0.5442 | 0.5108 |
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| 1.1363 | 3.0 | 801 | 1.1585 | 0.5758 | 0.5715 | 0.5758 | 0.5638 |
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| 1.0894 | 4.0 | 1068 | 1.1087 | 0.5912 | 0.5827 | 0.5912 | 0.5706 |
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| 1.0666 | 5.0 | 1335 | 1.0655 | 0.6184 | 0.6111 | 0.6184 | 0.6082 |
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| 0.9219 | 6.0 | 1602 | 1.0520 | 0.6233 | 0.6153 | 0.6233 | 0.6136 |
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| 0.943 | 7.0 | 1869 | 1.0331 | 0.6299 | 0.6238 | 0.6299 | 0.6231 |
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| 0.8906 | 8.0 | 2136 | 1.0238 | 0.6318 | 0.6252 | 0.6318 | 0.6239 |
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| 0.8854 | 9.0 | 2403 | 1.0196 | 0.6341 | 0.6313 | 0.6341 | 0.6298 |
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| 0.8991 | 10.0 | 2670 | 1.0183 | 0.6362 | 0.6312 | 0.6362 | 0.6310 |
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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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