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--- |
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license: apache-2.0 |
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base_model: pradanaadn/vit-emotional-classifier |
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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-emotional-classifier |
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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: 0.65625 |
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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-emotional-classifier |
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This model is a fine-tuned version of [pradanaadn/vit-emotional-classifier](https://huggingface.co/pradanaadn/vit-emotional-classifier) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1495 |
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- Accuracy: 0.6562 |
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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: 5 |
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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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| 0.4801 | 0.5 | 20 | 1.2238 | 0.5875 | |
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| 0.4681 | 1.0 | 40 | 1.2062 | 0.6188 | |
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| 0.3414 | 1.5 | 60 | 1.1674 | 0.6 | |
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| 0.2972 | 2.0 | 80 | 1.1362 | 0.6125 | |
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| 0.2503 | 2.5 | 100 | 1.1508 | 0.6 | |
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| 0.1872 | 3.0 | 120 | 1.1495 | 0.6562 | |
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| 0.1929 | 3.5 | 140 | 1.1998 | 0.5875 | |
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| 0.1883 | 4.0 | 160 | 1.2023 | 0.5938 | |
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| 0.1729 | 4.5 | 180 | 1.2130 | 0.6 | |
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| 0.2007 | 5.0 | 200 | 1.2021 | 0.5813 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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