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tiny-random-vit-finetuned-eurosat
This model is a fine-tuned version of hf-internal-testing/tiny-random-vit on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0488
- Accuracy: 0.6647
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 |
|---|---|---|---|---|
| 1.1192 | 0.99 | 70 | 1.0867 | 0.6627 |
| 1.067 | 1.99 | 140 | 1.0563 | 0.6657 |
| 0.9719 | 2.99 | 210 | 1.0488 | 0.6647 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
