resnet-50-finetuned-eurosat
This model is a fine-tuned version of MF21377197/resnet-50-finetuned-eurosat on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 21.6578
- Accuracy: 0.5284
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: 1e-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: 12
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
19.4471 | 1.0 | 351 | 25.2381 | 0.4514 |
14.378 | 2.0 | 703 | 24.5923 | 0.4594 |
20.7257 | 3.0 | 1055 | 24.3360 | 0.4706 |
23.0579 | 4.0 | 1407 | 17.9277 | 0.479 |
16.7616 | 5.0 | 1758 | 24.0013 | 0.4808 |
13.2407 | 6.0 | 2110 | 16.8144 | 0.4888 |
12.5439 | 7.0 | 2462 | 10.8161 | 0.496 |
10.301 | 8.0 | 2814 | 14.1573 | 0.5066 |
18.2068 | 9.0 | 3165 | 15.7831 | 0.5054 |
5.7088 | 10.0 | 3517 | 14.3309 | 0.512 |
18.9725 | 11.0 | 3869 | 21.6578 | 0.5284 |
16.9049 | 11.97 | 4212 | 12.9670 | 0.5204 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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