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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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- f1 |
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model-index: |
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- name: vit-molecul |
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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-molecul |
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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: 0.5737 |
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- Accuracy: 0.71 |
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- F1: 0.7086 |
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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: 3e-06 |
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- train_batch_size: 50 |
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- eval_batch_size: 50 |
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- seed: 42 |
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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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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.723 | 1.0 | 8 | 0.6790 | 0.61 | 0.6096 | |
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| 0.6915 | 2.0 | 16 | 0.6661 | 0.62 | 0.5924 | |
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| 0.6689 | 3.0 | 24 | 0.6470 | 0.69 | 0.6892 | |
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| 0.6517 | 4.0 | 32 | 0.6356 | 0.64 | 0.6377 | |
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| 0.6368 | 5.0 | 40 | 0.6289 | 0.72 | 0.7199 | |
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| 0.621 | 6.0 | 48 | 0.6217 | 0.73 | 0.7293 | |
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| 0.6061 | 7.0 | 56 | 0.6197 | 0.69 | 0.6862 | |
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| 0.5924 | 8.0 | 64 | 0.6087 | 0.73 | 0.7293 | |
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| 0.5767 | 9.0 | 72 | 0.6003 | 0.72 | 0.7199 | |
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| 0.5633 | 10.0 | 80 | 0.5953 | 0.72 | 0.7196 | |
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| 0.5491 | 11.0 | 88 | 0.5885 | 0.72 | 0.7199 | |
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| 0.5351 | 12.0 | 96 | 0.5869 | 0.71 | 0.7100 | |
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| 0.5239 | 13.0 | 104 | 0.5867 | 0.7 | 0.6995 | |
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| 0.5118 | 14.0 | 112 | 0.5804 | 0.71 | 0.7100 | |
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| 0.502 | 15.0 | 120 | 0.5752 | 0.71 | 0.7100 | |
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| 0.4942 | 16.0 | 128 | 0.5738 | 0.72 | 0.7199 | |
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| 0.4885 | 17.0 | 136 | 0.5771 | 0.71 | 0.7086 | |
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| 0.4831 | 18.0 | 144 | 0.5751 | 0.71 | 0.7086 | |
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| 0.4793 | 19.0 | 152 | 0.5743 | 0.71 | 0.7086 | |
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| 0.4774 | 20.0 | 160 | 0.5737 | 0.71 | 0.7086 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
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