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--- |
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license: apache-2.0 |
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base_model: facebook/dinov2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: dinov2-base-finetuned-ct-iq |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 1.0 |
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- name: F1 |
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type: f1 |
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value: 1.0 |
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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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# dinov2-base-finetuned-ct-iq |
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This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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- Accuracy: 1.0 |
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- F1: 1.0 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 0.0265 | 0.9954 | 162 | 0.2460 | 0.9233 | 0.9295 | |
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| 0.0185 | 1.9969 | 325 | 0.0023 | 1.0 | 1.0 | |
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| 0.1076 | 2.9985 | 488 | 0.0204 | 0.9939 | 0.9938 | |
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| 0.1424 | 4.0 | 651 | 0.0001 | 1.0 | 1.0 | |
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| 0.0002 | 4.9954 | 813 | 0.0013 | 1.0 | 1.0 | |
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| 0.0414 | 5.9969 | 976 | 0.0000 | 1.0 | 1.0 | |
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| 0.0003 | 6.9985 | 1139 | 0.0003 | 1.0 | 1.0 | |
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| 0.0011 | 8.0 | 1302 | 0.0163 | 0.9969 | 0.9969 | |
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| 0.0 | 8.9954 | 1464 | 0.0010 | 1.0 | 1.0 | |
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| 0.0 | 9.9539 | 1620 | 0.0000 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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