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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: 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: 0.525 |
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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: 1.4782 |
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- Accuracy: 0.525 |
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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: 2 |
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- total_train_batch_size: 64 |
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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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| 2.0776 | 1.0 | 10 | 2.0731 | 0.1437 | |
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| 2.0526 | 2.0 | 20 | 2.0567 | 0.1688 | |
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| 1.9975 | 3.0 | 30 | 2.0160 | 0.2 | |
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| 1.8977 | 4.0 | 40 | 1.9550 | 0.3 | |
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| 1.778 | 5.0 | 50 | 1.8805 | 0.3625 | |
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| 1.6549 | 6.0 | 60 | 1.8073 | 0.375 | |
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| 1.5379 | 7.0 | 70 | 1.7428 | 0.4125 | |
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| 1.4241 | 8.0 | 80 | 1.6957 | 0.4062 | |
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| 1.3212 | 9.0 | 90 | 1.6550 | 0.45 | |
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| 1.2245 | 10.0 | 100 | 1.6271 | 0.4437 | |
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| 1.1336 | 11.0 | 110 | 1.5928 | 0.4562 | |
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| 1.0483 | 12.0 | 120 | 1.5695 | 0.4688 | |
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| 0.9669 | 13.0 | 130 | 1.5452 | 0.4875 | |
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| 0.8889 | 14.0 | 140 | 1.5248 | 0.4875 | |
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| 0.815 | 15.0 | 150 | 1.5063 | 0.5062 | |
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| 0.7466 | 16.0 | 160 | 1.4909 | 0.4938 | |
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| 0.6852 | 17.0 | 170 | 1.4782 | 0.525 | |
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| 0.6308 | 18.0 | 180 | 1.4615 | 0.5 | |
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| 0.5819 | 19.0 | 190 | 1.4541 | 0.5 | |
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| 0.5392 | 20.0 | 200 | 1.4458 | 0.5125 | |
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| 0.503 | 21.0 | 210 | 1.4393 | 0.5 | |
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| 0.4718 | 22.0 | 220 | 1.4289 | 0.5188 | |
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| 0.4458 | 23.0 | 230 | 1.4238 | 0.5188 | |
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| 0.4234 | 24.0 | 240 | 1.4211 | 0.5125 | |
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| 0.405 | 25.0 | 250 | 1.4182 | 0.5 | |
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| 0.3905 | 26.0 | 260 | 1.4157 | 0.5062 | |
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| 0.379 | 27.0 | 270 | 1.4125 | 0.5062 | |
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| 0.3706 | 28.0 | 280 | 1.4119 | 0.5062 | |
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| 0.3649 | 29.0 | 290 | 1.4115 | 0.5062 | |
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| 0.3618 | 30.0 | 300 | 1.4111 | 0.5062 | |
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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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