vit-base-patch16-224-finetuned-eurosat
This model is a fine-tuned version of google/vit-base-patch16-224 on the None dataset. It achieves the following results on the evaluation set:
- Loss: inf
- Accuracy: 0.0224
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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 384
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 18403482038360886413349920928956416.0000 | 1.0 | 258 | inf | 0.0224 |
| 18462639726606223815285376672595968.0000 | 2.0 | 517 | inf | 0.0224 |
| 18309578839444917002657010957680640.0000 | 3.0 | 775 | inf | 0.0224 |
| 18496480055520128970480019132383232.0000 | 4.0 | 1034 | inf | 0.0224 |
| 18428848915293890075301730177777664.0000 | 4.99 | 1290 | inf | 0.0224 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for brainer/vit-base-patch16-224-finetuned-eurosat
Base model
google/vit-base-patch16-224