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dinov2-base-finetuned-lora-EA-rank8

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

  • Loss: 0.4365
  • Accuracy: 0.8233

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: 0.0001
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 1024
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.7805 2 0.5030 0.8142
No log 1.9512 5 0.4567 0.8215
No log 2.7317 7 0.4511 0.8215
0.4811 3.9024 10 0.4438 0.8179
0.4811 4.6829 12 0.4392 0.8215
0.4811 5.8537 15 0.4379 0.8452
0.4811 6.6341 17 0.4365 0.8233

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.1.2
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Model size
87M params
Tensor type
F32
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