beit-base-patch16-224-pt22k-finetuned-eurosat
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3045
- Accuracy: 0.8586
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 | 0.5181 | 0.7071 |
0.6727 | 2.0 | 14 | 0.4030 | 0.8182 |
0.3522 | 3.0 | 21 | 0.3045 | 0.8586 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.2.0
- Tokenizers 0.12.1
- Downloads last month
- 21
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.