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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-ODIR-5K |
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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: test |
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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: 0.7188755020080321 |
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- name: F1 |
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type: f1 |
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value: 0.6332945285215367 |
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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-ODIR-5K |
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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: 0.5700 |
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- Accuracy: 0.7189 |
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- F1: 0.6333 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 6 |
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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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| 0.6374 | 0.9858 | 52 | 0.6186 | 0.6778 | 0.2031 | |
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| 0.5789 | 1.9905 | 105 | 0.5661 | 0.7153 | 0.3794 | |
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| 0.5368 | 2.9953 | 158 | 0.5334 | 0.7407 | 0.5756 | |
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| 0.4162 | 4.0 | 211 | 0.5747 | 0.6983 | 0.6198 | |
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| 0.3679 | 4.9858 | 263 | 0.5700 | 0.7189 | 0.6333 | |
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| 0.2431 | 5.9147 | 312 | 0.6111 | 0.7564 | 0.6331 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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