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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-patch16-224-dmae-va-U5-42B |
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results: [] |
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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-dmae-va-U5-42B |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8695 |
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- Accuracy: 0.7667 |
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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-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: 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: 42 |
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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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| No log | 0.9 | 7 | 1.3101 | 0.4667 | |
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| 1.408 | 1.94 | 15 | 1.1884 | 0.4833 | |
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| 1.1286 | 2.97 | 23 | 0.9476 | 0.5167 | |
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| 0.7589 | 4.0 | 31 | 0.7637 | 0.75 | |
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| 0.7589 | 4.9 | 38 | 0.7186 | 0.6833 | |
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| 0.4786 | 5.94 | 46 | 0.6192 | 0.7833 | |
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| 0.2874 | 6.97 | 54 | 0.6195 | 0.7833 | |
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| 0.2027 | 8.0 | 62 | 0.5959 | 0.7833 | |
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| 0.2027 | 8.9 | 69 | 0.6104 | 0.7667 | |
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| 0.1662 | 9.94 | 77 | 0.7297 | 0.75 | |
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| 0.1462 | 10.97 | 85 | 0.7852 | 0.7667 | |
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| 0.1419 | 12.0 | 93 | 0.8637 | 0.7167 | |
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| 0.1199 | 12.9 | 100 | 0.6797 | 0.7333 | |
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| 0.1199 | 13.94 | 108 | 0.7660 | 0.7667 | |
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| 0.0949 | 14.97 | 116 | 0.7386 | 0.7167 | |
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| 0.0901 | 16.0 | 124 | 1.0126 | 0.7 | |
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| 0.0808 | 16.9 | 131 | 0.7060 | 0.8 | |
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| 0.0808 | 17.94 | 139 | 0.7857 | 0.7833 | |
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| 0.102 | 18.97 | 147 | 0.7411 | 0.8 | |
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| 0.0706 | 20.0 | 155 | 0.7340 | 0.8167 | |
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| 0.0582 | 20.9 | 162 | 0.8589 | 0.75 | |
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| 0.0687 | 21.94 | 170 | 0.8546 | 0.7667 | |
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| 0.0687 | 22.97 | 178 | 0.7761 | 0.7667 | |
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| 0.0633 | 24.0 | 186 | 0.8112 | 0.7667 | |
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| 0.0626 | 24.9 | 193 | 0.6943 | 0.8333 | |
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| 0.0578 | 25.94 | 201 | 0.8593 | 0.7833 | |
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| 0.0578 | 26.97 | 209 | 0.7215 | 0.85 | |
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| 0.0434 | 28.0 | 217 | 0.8150 | 0.8 | |
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| 0.0492 | 28.9 | 224 | 0.7834 | 0.7833 | |
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| 0.0582 | 29.94 | 232 | 0.7844 | 0.7833 | |
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| 0.0515 | 30.97 | 240 | 0.7973 | 0.7667 | |
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| 0.0515 | 32.0 | 248 | 0.7744 | 0.8 | |
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| 0.0487 | 32.9 | 255 | 0.8614 | 0.75 | |
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| 0.0455 | 33.94 | 263 | 0.8195 | 0.7667 | |
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| 0.0329 | 34.97 | 271 | 0.8327 | 0.7667 | |
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| 0.0329 | 36.0 | 279 | 0.8889 | 0.7667 | |
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| 0.0447 | 36.9 | 286 | 0.8705 | 0.7667 | |
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| 0.0445 | 37.94 | 294 | 0.8695 | 0.7667 | |
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### Framework versions |
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- Transformers 4.38.2 |
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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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