metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: wmc-wmk811-v0-vit-special_map_det_0917
results: []
wmc-wmk811-v0-vit-special_map_det_0917
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: 0.0354
- Accuracy: 0.9882
- Precision: 0.9872
- Recall: 0.9854
- F1: 0.9863
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0471 | 0.2158 | 400 | 0.0651 | 0.9766 | 0.9793 | 0.9662 | 0.9724 |
| 0.0664 | 0.4317 | 800 | 0.0445 | 0.9874 | 0.9879 | 0.9828 | 0.9853 |
| 0.0391 | 0.6475 | 1200 | 0.0476 | 0.9833 | 0.9826 | 0.9785 | 0.9805 |
| 0.0478 | 0.8633 | 1600 | 0.0354 | 0.9882 | 0.9872 | 0.9854 | 0.9863 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1