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: 0.6217
- Accuracy: 0.8601
- F1: 0.8587
- Precision: 0.8603
- Recall: 0.8601
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: 16
- 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 |
|---|---|---|---|---|---|---|---|
| 0.1753 | 1.0 | 626 | 0.3718 | 0.8290 | 0.8323 | 0.8513 | 0.8290 |
| 0.1849 | 2.0 | 1252 | 0.4400 | 0.8342 | 0.8309 | 0.8292 | 0.8342 |
| 0.0853 | 3.0 | 1878 | 0.5032 | 0.8135 | 0.8171 | 0.8278 | 0.8135 |
| 0.0046 | 4.0 | 2504 | 0.5403 | 0.8601 | 0.8615 | 0.8655 | 0.8601 |
| 0.0002 | 5.0 | 3130 | 0.5898 | 0.8601 | 0.8587 | 0.8603 | 0.8601 |
| 0.0002 | 6.0 | 3756 | 0.6217 | 0.8601 | 0.8587 | 0.8603 | 0.8601 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.13.3