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--- |
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license: apache-2.0 |
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base_model: facebook/vit-mae-base |
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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-mae-base-effusion-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: 0.8173673328738801 |
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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-mae-base-effusion-classifier |
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This model is a fine-tuned version of [facebook/vit-mae-base](https://huggingface.co/facebook/vit-mae-base) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4179 |
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- Accuracy: 0.8174 |
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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: 5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 0.2 |
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- num_epochs: 20 |
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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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| 0.6554 | 1.0 | 362 | 0.6692 | 0.6030 | |
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| 0.569 | 2.0 | 725 | 0.5891 | 0.7023 | |
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| 0.6098 | 3.0 | 1088 | 0.5421 | 0.7367 | |
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| 0.4984 | 4.0 | 1451 | 0.5668 | 0.7043 | |
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| 0.4884 | 5.0 | 1813 | 0.6061 | 0.6844 | |
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| 0.4351 | 6.0 | 2176 | 0.4481 | 0.8098 | |
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| 0.4794 | 7.0 | 2539 | 0.4384 | 0.8084 | |
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| 0.4636 | 8.0 | 2902 | 0.4343 | 0.8077 | |
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| 0.4816 | 9.0 | 3264 | 0.5363 | 0.7491 | |
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| 0.5016 | 10.0 | 3627 | 0.4993 | 0.7677 | |
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| 0.4826 | 11.0 | 3990 | 0.4483 | 0.8043 | |
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| 0.4707 | 12.0 | 4353 | 0.4249 | 0.8112 | |
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| 0.4483 | 13.0 | 4715 | 0.4193 | 0.8160 | |
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| 0.419 | 14.0 | 5078 | 0.4146 | 0.8215 | |
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| 0.5039 | 15.0 | 5441 | 0.4188 | 0.8181 | |
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| 0.4111 | 16.0 | 5804 | 0.4459 | 0.8112 | |
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| 0.3293 | 17.0 | 6166 | 0.4228 | 0.8181 | |
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| 0.4171 | 18.0 | 6529 | 0.4239 | 0.8215 | |
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| 0.3375 | 19.0 | 6892 | 0.4162 | 0.8215 | |
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| 0.32 | 19.96 | 7240 | 0.4179 | 0.8174 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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