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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- rock-glacier-dataset |
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metrics: |
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- accuracy |
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model-index: |
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- name: skynet |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: rock-glacier-dataset |
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type: rock-glacier-dataset |
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config: image-classification |
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split: train |
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args: image-classification |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9688888888888889 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# skynet |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the rock-glacier-dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1080 |
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- Accuracy: 0.9689 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.4521 | 0.3 | 75 | 0.4436 | 0.824 | |
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| 0.3561 | 0.61 | 150 | 0.2802 | 0.9244 | |
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| 0.2306 | 0.91 | 225 | 0.2124 | 0.9307 | |
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| 0.1621 | 1.21 | 300 | 0.1695 | 0.9458 | |
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| 0.1396 | 1.52 | 375 | 0.1589 | 0.9476 | |
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| 0.1157 | 1.82 | 450 | 0.1342 | 0.9547 | |
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| 0.0707 | 2.13 | 525 | 0.1342 | 0.96 | |
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| 0.0578 | 2.43 | 600 | 0.1294 | 0.9591 | |
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| 0.0687 | 2.73 | 675 | 0.1285 | 0.9609 | |
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| 0.0431 | 3.04 | 750 | 0.1066 | 0.9671 | |
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| 0.0249 | 3.34 | 825 | 0.1069 | 0.968 | |
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| 0.0614 | 3.64 | 900 | 0.1073 | 0.968 | |
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| 0.0469 | 3.95 | 975 | 0.1080 | 0.9689 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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