mit-b0-finetuned-eurosat
This model is a fine-tuned version of nvidia/mit-b0 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1782
- Accuracy: 0.9495
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 0.3828 | 0.8081 |
| 0.4864 | 2.0 | 14 | 0.2224 | 0.9192 |
| 0.2035 | 3.0 | 21 | 0.1782 | 0.9495 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.2.0
- Tokenizers 0.12.1