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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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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-emotion |
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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: 0.61875 |
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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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# vit-emotion |
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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: 1.1858 |
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- Accuracy: 0.6188 |
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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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- 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: 20 |
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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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| 1.8403 | 1.0 | 40 | 1.7317 | 0.3063 | |
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| 1.4783 | 2.0 | 80 | 1.5047 | 0.4938 | |
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| 1.1866 | 3.0 | 120 | 1.3522 | 0.55 | |
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| 0.8581 | 4.0 | 160 | 1.2084 | 0.575 | |
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| 0.6056 | 5.0 | 200 | 1.2348 | 0.5375 | |
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| 0.3745 | 6.0 | 240 | 1.2119 | 0.5625 | |
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| 0.2129 | 7.0 | 280 | 1.2012 | 0.5437 | |
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| 0.1547 | 8.0 | 320 | 1.2181 | 0.5875 | |
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| 0.1216 | 9.0 | 360 | 1.2196 | 0.5875 | |
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| 0.1023 | 10.0 | 400 | 1.1858 | 0.6188 | |
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| 0.102 | 11.0 | 440 | 1.2190 | 0.5938 | |
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| 0.083 | 12.0 | 480 | 1.2149 | 0.6125 | |
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| 0.0917 | 13.0 | 520 | 1.2600 | 0.5875 | |
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| 0.0807 | 14.0 | 560 | 1.2367 | 0.6062 | |
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| 0.0741 | 15.0 | 600 | 1.2382 | 0.6 | |
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| 0.0721 | 16.0 | 640 | 1.2464 | 0.5875 | |
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| 0.0678 | 17.0 | 680 | 1.2548 | 0.5938 | |
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| 0.0752 | 18.0 | 720 | 1.2591 | 0.5875 | |
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| 0.0657 | 19.0 | 760 | 1.2590 | 0.6062 | |
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| 0.0643 | 20.0 | 800 | 1.2589 | 0.5938 | |
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### Framework versions |
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- Transformers 4.42.4 |
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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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