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--- |
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license: apache-2.0 |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: hq_fer2013 |
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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: 0.7022445455972375 |
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- name: Precision |
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type: precision |
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value: 0.7038651811268685 |
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- name: Recall |
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type: recall |
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value: 0.7022445455972375 |
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- name: F1 |
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type: f1 |
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value: 0.702185081437324 |
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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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# hq_fer2013 |
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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: 0.8438 |
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- Accuracy: 0.7022 |
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- Precision: 0.7039 |
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- Recall: 0.7022 |
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- F1: 0.7022 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 17 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 13 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.3081 | 1.0 | 398 | 1.3132 | 0.5555 | 0.5079 | 0.5555 | 0.5137 | |
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| 0.991 | 2.0 | 796 | 1.0141 | 0.6332 | 0.6356 | 0.6332 | 0.6153 | |
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| 0.9099 | 3.0 | 1194 | 0.9257 | 0.6682 | 0.6677 | 0.6682 | 0.6631 | |
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| 0.8306 | 4.0 | 1592 | 0.8832 | 0.6765 | 0.6838 | 0.6765 | 0.6747 | |
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| 0.7755 | 5.0 | 1990 | 0.8583 | 0.6892 | 0.6896 | 0.6892 | 0.6876 | |
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| 0.7129 | 6.0 | 2388 | 0.8442 | 0.6931 | 0.6951 | 0.6931 | 0.6922 | |
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| 0.6549 | 7.0 | 2786 | 0.8494 | 0.6952 | 0.7054 | 0.6952 | 0.6978 | |
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| 0.6246 | 8.0 | 3184 | 0.8394 | 0.6963 | 0.7023 | 0.6963 | 0.6977 | |
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| 0.6138 | 9.0 | 3582 | 0.8421 | 0.6996 | 0.7080 | 0.6996 | 0.7013 | |
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| 0.5824 | 10.0 | 3980 | 0.8438 | 0.7022 | 0.7039 | 0.7022 | 0.7022 | |
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| 0.5517 | 11.0 | 4378 | 0.8497 | 0.7002 | 0.7034 | 0.7002 | 0.7005 | |
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| 0.5154 | 12.0 | 4776 | 0.8508 | 0.7021 | 0.7030 | 0.7021 | 0.7018 | |
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| 0.5318 | 13.0 | 5174 | 0.8540 | 0.7010 | 0.7029 | 0.7010 | 0.7013 | |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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