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Dinov2 Base Finetuned SkinDisease

This model is a fine-tuned version of facebook/dinov2-base on the imagefolder dataset. It achieves the following results on the evaluation set: Loss: 1.0419 Accuracy: 0.8739 Precision: 0.8857 Recall: 0.8674 F1 Macro:...

KindOtherBase modelfacebook/dinov2-baseVersionRevision ebee824

Model source

Kind
Other
File size
331 MB
Base model
facebook/dinov2-base
Version
vRevision ebee824
Updated
Sep 17, 2026
Downloads
5
Source
Hugging Face

Source description

dinov2-base-finetuned-SkinDisease

This model is a fine-tuned version of facebook/dinov2-base on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0419
  • Accuracy: 0.8739
  • Precision: 0.8857
  • Recall: 0.8674
  • F1 Macro: 0.8739
  • F1 Weighted: 0.873

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-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1 MacroF1 Weighted
4.47241.0831.53230.68620.76160.72420.69510.6781
3.46392.01661.29990.79330.84670.81790.81460.7985
3.14613.02491.15960.8240.83020.82880.82070.8216
2.94594.03321.19390.83720.86070.82840.8340.8292
2.84445.04151.10710.85480.87140.85740.85950.8563
2.80956.04981.08690.86660.87080.85730.86150.8655
2.74227.05811.09860.85780.87660.85040.85750.8564
2.71118.06641.05450.87390.88560.87360.8770.8725
2.69909.07471.06560.8710.88290.86080.86730.8692
2.494910.08301.04190.87390.88570.86740.87390.873

Framework versions

  • Transformers 5.10.2
  • Pytorch 2.10.0+cu128
  • Datasets 4.8.5
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion ebee82472e524b860a0fe1fd8a38117ffd81a711
huggingface.co/RushnaFathima/dinov2-base-finetuned-SkinDisease/tree/ebee82472e524b860a0fe1fd8a38117ffd81a711

Verified Sep 17

Model artifacts

1 artifact

model.safetensors

safetensors · 331 MB · SHA-256 ee4dd6824726…ecda · Hugging Face

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Source excerpts

2 excerpts

--- library_name: transformers license: apache-2.0 base_model: facebook/dinov2-base tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy - precision - recall model-index: - name: dinov2-base-finetuned-SkinDisease results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: validation args: default metrics: - name: Accuracy type: accuracy value: 0.8739 - name: Precision type: precision value: 0.8857 - name: Recall type: recall value: 0.8674 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # dinov2-base-finetuned-SkinDisease This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.0419 - Accuracy: 0.8739 - Precision: 0.8857 - Recall: 0.8674 - F1 Macro: 0.8739 - F1 Weighted: 0.873 ## 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-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Macro | F1 Weighted | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:-----------:| | 4.4724 | 1.0 | 83 | 1.5323 | 0.6862 | 0.7616 | 0.7242 | 0.6951 | 0.6781 | | 3.4639 | 2.0 | 166 | 1.2999 | 0.7933 | 0.8467 | 0.8179 | 0.8146 | 0.7985 | | 3.1461 | 3.0 | 249 | 1.1596 | 0.824 | 0.8302 | 0.8288 | 0.8207 | 0.8216 | | 2.9459 | 4.0 | 332 | 1.1939 | 0.8372 | 0.8607 | 0.8284 | 0.834 | 0.8292 | | 2.8444 | 5.0 | 415 | 1.1071 | 0.8548 | 0.8714 | 0.8574 | 0.8595 | 0.8563 | | 2....

Source context: 5 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo RushnaFathima/dinov2-base-finetuned-SkinDisease