convnextv2-base-22k-224-finetuned-eurosat-50
This model is a fine-tuned version of facebook/convnextv2-base-22k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2875
- Accuracy: 0.9147
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.9019 | 1.0 | 122 | 1.9510 | 0.1727 |
1.7782 | 2.0 | 244 | 1.8239 | 0.3073 |
1.6214 | 3.0 | 366 | 1.6121 | 0.4913 |
1.3495 | 4.0 | 488 | 1.3064 | 0.6238 |
1.0994 | 5.0 | 610 | 1.0243 | 0.7163 |
0.8866 | 6.0 | 732 | 0.8165 | 0.7564 |
0.7282 | 7.0 | 854 | 0.6637 | 0.7996 |
0.6211 | 8.0 | 976 | 0.5623 | 0.8160 |
0.5114 | 9.0 | 1098 | 0.4681 | 0.8551 |
0.3835 | 10.0 | 1220 | 0.3917 | 0.8787 |
0.3543 | 11.0 | 1342 | 0.3122 | 0.9013 |
0.3534 | 12.0 | 1464 | 0.2875 | 0.9147 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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