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--- |
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library_name: transformers |
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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: emotion_classification |
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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: 0.475 |
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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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# emotion_classification |
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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: 1.5599 |
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- Accuracy: 0.475 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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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 | 5 | 2.0884 | 0.1125 | |
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| 2.08 | 2.0 | 10 | 2.0750 | 0.1437 | |
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| 2.08 | 3.0 | 15 | 2.0519 | 0.2125 | |
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| 2.0091 | 4.0 | 20 | 2.0177 | 0.225 | |
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| 2.0091 | 5.0 | 25 | 1.9777 | 0.2625 | |
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| 1.8779 | 6.0 | 30 | 1.9381 | 0.3125 | |
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| 1.8779 | 7.0 | 35 | 1.8990 | 0.3438 | |
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| 1.7355 | 8.0 | 40 | 1.8592 | 0.3688 | |
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| 1.7355 | 9.0 | 45 | 1.8217 | 0.3812 | |
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| 1.598 | 10.0 | 50 | 1.7844 | 0.4 | |
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| 1.598 | 11.0 | 55 | 1.7536 | 0.4062 | |
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| 1.4689 | 12.0 | 60 | 1.7217 | 0.4188 | |
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| 1.4689 | 13.0 | 65 | 1.7019 | 0.4188 | |
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| 1.3534 | 14.0 | 70 | 1.6773 | 0.4188 | |
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| 1.3534 | 15.0 | 75 | 1.6614 | 0.425 | |
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| 1.2526 | 16.0 | 80 | 1.6448 | 0.4562 | |
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| 1.2526 | 17.0 | 85 | 1.6306 | 0.45 | |
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| 1.1657 | 18.0 | 90 | 1.6201 | 0.4562 | |
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| 1.1657 | 19.0 | 95 | 1.6067 | 0.4562 | |
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| 1.0918 | 20.0 | 100 | 1.5992 | 0.45 | |
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| 1.0918 | 21.0 | 105 | 1.5889 | 0.4562 | |
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| 1.0311 | 22.0 | 110 | 1.5852 | 0.4562 | |
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| 1.0311 | 23.0 | 115 | 1.5767 | 0.4625 | |
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| 0.9814 | 24.0 | 120 | 1.5733 | 0.45 | |
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| 0.9814 | 25.0 | 125 | 1.5688 | 0.4625 | |
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| 0.9439 | 26.0 | 130 | 1.5643 | 0.4562 | |
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| 0.9439 | 27.0 | 135 | 1.5620 | 0.4625 | |
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| 0.918 | 28.0 | 140 | 1.5599 | 0.475 | |
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| 0.918 | 29.0 | 145 | 1.5586 | 0.4625 | |
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| 0.9044 | 30.0 | 150 | 1.5582 | 0.4562 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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