metadata
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-base-patch32-finetuned-eurosat
results: []
clip-vit-base-patch32-finetuned-eurosat
This model is a fine-tuned version of openai/clip-vit-base-patch32 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0987
- Accuracy: 0.9716
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4295 | 0.9979 | 351 | 0.2629 | 0.915 |
| 0.4167 | 1.9986 | 703 | 0.2365 | 0.9222 |
| 0.4104 | 2.9993 | 1055 | 0.2205 | 0.9252 |
| 0.3847 | 4.0 | 1407 | 0.1917 | 0.9338 |
| 0.3928 | 4.9979 | 1758 | 0.1803 | 0.9414 |
| 0.311 | 5.9986 | 2110 | 0.1429 | 0.9524 |
| 0.2614 | 6.9993 | 2462 | 0.1137 | 0.961 |
| 0.2579 | 8.0 | 2814 | 0.1102 | 0.9638 |
| 0.1993 | 8.9979 | 3165 | 0.1037 | 0.9688 |
| 0.1921 | 9.9787 | 3510 | 0.0987 | 0.9716 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1