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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: 20E-affecthq |
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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: 0.7188003869719445 |
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- name: Precision |
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type: precision |
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value: 0.7219837313936599 |
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- name: Recall |
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type: recall |
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value: 0.7188003869719445 |
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- name: F1 |
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type: f1 |
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value: 0.718989971086903 |
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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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# 20E-affecthq |
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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: 0.8271 |
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- Accuracy: 0.7188 |
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- Precision: 0.7220 |
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- Recall: 0.7188 |
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- F1: 0.7190 |
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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: 20 |
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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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| 1.9149 | 1.0 | 194 | 1.8887 | 0.3750 | 0.3413 | 0.3750 | 0.3045 | |
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| 1.2903 | 2.0 | 388 | 1.2485 | 0.5792 | 0.5726 | 0.5792 | 0.5526 | |
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| 1.071 | 3.0 | 582 | 1.0587 | 0.6321 | 0.6258 | 0.6321 | 0.6228 | |
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| 1.0185 | 4.0 | 776 | 0.9817 | 0.6617 | 0.6584 | 0.6617 | 0.6553 | |
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| 0.894 | 5.0 | 970 | 0.9293 | 0.6869 | 0.6872 | 0.6869 | 0.6820 | |
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| 0.8283 | 6.0 | 1164 | 0.8881 | 0.6936 | 0.6929 | 0.6936 | 0.6905 | |
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| 0.8185 | 7.0 | 1358 | 0.8659 | 0.6982 | 0.7011 | 0.6982 | 0.6988 | |
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| 0.7499 | 8.0 | 1552 | 0.8558 | 0.7046 | 0.7050 | 0.7046 | 0.7021 | |
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| 0.7219 | 9.0 | 1746 | 0.8399 | 0.7124 | 0.7165 | 0.7124 | 0.7127 | |
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| 0.7382 | 10.0 | 1940 | 0.8300 | 0.7159 | 0.7184 | 0.7159 | 0.7145 | |
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| 0.6392 | 11.0 | 2134 | 0.8329 | 0.7088 | 0.7135 | 0.7088 | 0.7095 | |
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| 0.6549 | 12.0 | 2328 | 0.8297 | 0.7133 | 0.7135 | 0.7133 | 0.7120 | |
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| 0.6762 | 13.0 | 2522 | 0.8180 | 0.7156 | 0.7162 | 0.7156 | 0.7153 | |
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| 0.5937 | 14.0 | 2716 | 0.8271 | 0.7188 | 0.7220 | 0.7188 | 0.7190 | |
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| 0.569 | 15.0 | 2910 | 0.8245 | 0.7178 | 0.7175 | 0.7178 | 0.7165 | |
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| 0.5623 | 16.0 | 3104 | 0.8228 | 0.7165 | 0.7153 | 0.7165 | 0.7157 | |
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| 0.5291 | 17.0 | 3298 | 0.8238 | 0.7162 | 0.7165 | 0.7162 | 0.7156 | |
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| 0.5775 | 18.0 | 3492 | 0.8246 | 0.7153 | 0.7162 | 0.7153 | 0.7151 | |
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| 0.545 | 19.0 | 3686 | 0.8257 | 0.7178 | 0.7192 | 0.7178 | 0.7174 | |
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| 0.5409 | 20.0 | 3880 | 0.8245 | 0.7178 | 0.7187 | 0.7178 | 0.7177 | |
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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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