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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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- f1 |
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model-index: |
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- name: vit-base-patch16-224-in21k-finetuned-mgasior-07-02-2024 |
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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: F1 |
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type: f1 |
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value: 0.7716535433070866 |
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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-base-patch16-224-in21k-finetuned-mgasior-07-02-2024 |
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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: 0.8842 |
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- F1: 0.7717 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 1.731 | 0.98 | 35 | 1.6748 | 0.3386 | |
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| 1.5196 | 1.99 | 71 | 1.4890 | 0.4173 | |
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| 1.3727 | 2.99 | 107 | 1.2938 | 0.5276 | |
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| 1.2194 | 4.0 | 143 | 1.1519 | 0.6457 | |
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| 1.1538 | 4.98 | 178 | 1.0544 | 0.6693 | |
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| 1.0379 | 5.99 | 214 | 0.9852 | 0.7165 | |
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| 1.0232 | 6.99 | 250 | 0.9439 | 0.7323 | |
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| 0.9586 | 8.0 | 286 | 0.9136 | 0.7480 | |
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| 0.9374 | 8.98 | 321 | 0.8946 | 0.7638 | |
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| 0.96 | 9.79 | 350 | 0.8842 | 0.7717 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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