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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-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: 0.575 |
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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-Classifier |
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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: 1.3652 |
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- Accuracy: 0.575 |
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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: 30 |
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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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| No log | 1.0 | 40 | 1.8992 | 0.3312 | |
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| No log | 2.0 | 80 | 1.5939 | 0.4062 | |
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| No log | 3.0 | 120 | 1.4776 | 0.4688 | |
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| No log | 4.0 | 160 | 1.4012 | 0.4813 | |
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| No log | 5.0 | 200 | 1.3471 | 0.4875 | |
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| No log | 6.0 | 240 | 1.2877 | 0.5375 | |
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| No log | 7.0 | 280 | 1.2598 | 0.575 | |
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| No log | 8.0 | 320 | 1.3595 | 0.4938 | |
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| No log | 9.0 | 360 | 1.2825 | 0.5375 | |
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| No log | 10.0 | 400 | 1.3291 | 0.5062 | |
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| No log | 11.0 | 440 | 1.2422 | 0.5563 | |
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| No log | 12.0 | 480 | 1.2659 | 0.575 | |
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| 1.0646 | 13.0 | 520 | 1.3048 | 0.5062 | |
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| 1.0646 | 14.0 | 560 | 1.2993 | 0.5563 | |
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| 1.0646 | 15.0 | 600 | 1.2935 | 0.5563 | |
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| 1.0646 | 16.0 | 640 | 1.3589 | 0.5437 | |
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| 1.0646 | 17.0 | 680 | 1.2447 | 0.5938 | |
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| 1.0646 | 18.0 | 720 | 1.3298 | 0.5563 | |
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| 1.0646 | 19.0 | 760 | 1.2829 | 0.6 | |
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| 1.0646 | 20.0 | 800 | 1.3092 | 0.5813 | |
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| 1.0646 | 21.0 | 840 | 1.2895 | 0.5875 | |
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| 1.0646 | 22.0 | 880 | 1.3810 | 0.5625 | |
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| 1.0646 | 23.0 | 920 | 1.3833 | 0.5563 | |
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| 1.0646 | 24.0 | 960 | 1.4841 | 0.5312 | |
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| 0.3074 | 25.0 | 1000 | 1.3619 | 0.6062 | |
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| 0.3074 | 26.0 | 1040 | 1.3776 | 0.5563 | |
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| 0.3074 | 27.0 | 1080 | 1.3917 | 0.5875 | |
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| 0.3074 | 28.0 | 1120 | 1.3585 | 0.575 | |
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| 0.3074 | 29.0 | 1160 | 1.3455 | 0.5625 | |
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| 0.3074 | 30.0 | 1200 | 1.4409 | 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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