metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: vit-focal-skin
results: []
vit-focal-skin
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4871
- Accuracy: 0.8705
- F1: 0.8762
- Precision: 0.8862
- Recall: 0.8705
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1966 | 1.0 | 626 | 0.3647 | 0.8290 | 0.8307 | 0.8431 | 0.8290 |
| 0.1434 | 2.0 | 1252 | 0.3884 | 0.8238 | 0.8259 | 0.8418 | 0.8238 |
| 0.058 | 3.0 | 1878 | 0.5064 | 0.8187 | 0.8137 | 0.8183 | 0.8187 |
| 0.02 | 4.0 | 2504 | 0.5477 | 0.8394 | 0.8431 | 0.8538 | 0.8394 |
| 0.0018 | 5.0 | 3130 | 0.4876 | 0.8705 | 0.8749 | 0.8864 | 0.8705 |
| 0.0003 | 6.0 | 3756 | 0.4871 | 0.8705 | 0.8762 | 0.8862 | 0.8705 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.13.3