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vit-base-patch16-224_album_vitVMMRdb_make_model_album_pred
This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4670
- Accuracy: 0.8781
- Precision: 0.8768
- Recall: 0.8781
- F1: 0.8758
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 3.5529 | 1.0 | 839 | 3.3687 | 0.3096 | 0.2809 | 0.3096 | 0.2246 |
| 1.7855 | 2.0 | 1678 | 1.6042 | 0.6378 | 0.6187 | 0.6378 | 0.5996 |
| 1.1054 | 3.0 | 2517 | 1.0105 | 0.7556 | 0.7512 | 0.7556 | 0.7385 |
| 0.8179 | 4.0 | 3356 | 0.7794 | 0.8033 | 0.8020 | 0.8033 | 0.7934 |
| 0.6057 | 5.0 | 4195 | 0.6479 | 0.8294 | 0.8274 | 0.8294 | 0.8212 |
| 0.4709 | 6.0 | 5034 | 0.5817 | 0.8478 | 0.8477 | 0.8478 | 0.8428 |
| 0.3962 | 7.0 | 5873 | 0.5333 | 0.8571 | 0.8570 | 0.8571 | 0.8527 |
| 0.346 | 8.0 | 6712 | 0.5073 | 0.8638 | 0.8647 | 0.8638 | 0.8615 |
| 0.2772 | 9.0 | 7551 | 0.4881 | 0.8681 | 0.8679 | 0.8681 | 0.8656 |
| 0.2136 | 10.0 | 8390 | 0.4777 | 0.8719 | 0.8718 | 0.8719 | 0.8689 |
| 0.1937 | 11.0 | 9229 | 0.4737 | 0.8734 | 0.8731 | 0.8734 | 0.8703 |
| 0.1754 | 12.0 | 10068 | 0.4604 | 0.8758 | 0.8750 | 0.8758 | 0.8733 |
| 0.1111 | 13.0 | 10907 | 0.4561 | 0.8790 | 0.8782 | 0.8790 | 0.8768 |
| 0.1128 | 14.0 | 11746 | 0.4519 | 0.8808 | 0.8799 | 0.8808 | 0.8787 |
| 0.1018 | 15.0 | 12585 | 0.4497 | 0.8813 | 0.8805 | 0.8813 | 0.8794 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
