metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-vit
results: []
test-vit
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: 0.2285
- Accuracy: 0.9970
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: 6e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.84 | 4 | 0.7136 | 0.9909 |
| No log | 1.89 | 9 | 0.4919 | 0.9939 |
| 0.6427 | 2.95 | 14 | 0.3749 | 0.9970 |
| 0.6427 | 4.0 | 19 | 0.3094 | 0.9939 |
| 0.3516 | 4.84 | 23 | 0.2767 | 0.9970 |
| 0.3516 | 5.89 | 28 | 0.2496 | 0.9970 |
| 0.2484 | 6.95 | 33 | 0.2357 | 0.9970 |
| 0.2484 | 8.0 | 38 | 0.2295 | 0.9970 |
| 0.2147 | 8.42 | 40 | 0.2285 | 0.9970 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2