<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
vit-molecul
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5737
- Accuracy: 0.71
- F1: 0.7086
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-06
- train_batch_size: 50
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.723 | 1.0 | 8 | 0.6790 | 0.61 | 0.6096 |
| 0.6915 | 2.0 | 16 | 0.6661 | 0.62 | 0.5924 |
| 0.6689 | 3.0 | 24 | 0.6470 | 0.69 | 0.6892 |
| 0.6517 | 4.0 | 32 | 0.6356 | 0.64 | 0.6377 |
| 0.6368 | 5.0 | 40 | 0.6289 | 0.72 | 0.7199 |
| 0.621 | 6.0 | 48 | 0.6217 | 0.73 | 0.7293 |
| 0.6061 | 7.0 | 56 | 0.6197 | 0.69 | 0.6862 |
| 0.5924 | 8.0 | 64 | 0.6087 | 0.73 | 0.7293 |
| 0.5767 | 9.0 | 72 | 0.6003 | 0.72 | 0.7199 |
| 0.5633 | 10.0 | 80 | 0.5953 | 0.72 | 0.7196 |
| 0.5491 | 11.0 | 88 | 0.5885 | 0.72 | 0.7199 |
| 0.5351 | 12.0 | 96 | 0.5869 | 0.71 | 0.7100 |
| 0.5239 | 13.0 | 104 | 0.5867 | 0.7 | 0.6995 |
| 0.5118 | 14.0 | 112 | 0.5804 | 0.71 | 0.7100 |
| 0.502 | 15.0 | 120 | 0.5752 | 0.71 | 0.7100 |
| 0.4942 | 16.0 | 128 | 0.5738 | 0.72 | 0.7199 |
| 0.4885 | 17.0 | 136 | 0.5771 | 0.71 | 0.7086 |
| 0.4831 | 18.0 | 144 | 0.5751 | 0.71 | 0.7086 |
| 0.4793 | 19.0 | 152 | 0.5743 | 0.71 | 0.7086 |
| 0.4774 | 20.0 | 160 | 0.5737 | 0.71 | 0.7086 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.1
- Tokenizers 0.13.3
