metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-electrical-images
results: []
finetuned-electrical-images
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: 0.3677
- Accuracy: 0.8960
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7151 | 0.4651 | 100 | 0.5809 | 0.8201 |
| 0.6882 | 0.9302 | 200 | 0.4639 | 0.8498 |
| 0.3897 | 1.3953 | 300 | 0.4704 | 0.8465 |
| 0.4909 | 1.8605 | 400 | 0.5023 | 0.8449 |
| 0.2836 | 2.3256 | 500 | 0.4100 | 0.8746 |
| 0.2669 | 2.7907 | 600 | 0.3389 | 0.8993 |
| 0.2304 | 3.2558 | 700 | 0.3669 | 0.8927 |
| 0.1523 | 3.7209 | 800 | 0.3677 | 0.8960 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1