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Evaluation on the test set completed on 2024_10_25.
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metadata
license: apache-2.0
base_model: facebook/dinov2-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: DinoVdeau-large-2024_10_25-prova_batch-size8_freeze_monolabel
    results: []

DinoVdeau-large-2024_10_25-prova_batch-size8_freeze_monolabel

This model is a fine-tuned version of facebook/dinov2-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8116
  • F1 Micro: 0.5
  • F1 Macro: 0.2126
  • Accuracy: 0.5
  • Learning Rate: 0.001

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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Micro F1 Macro Accuracy Rate
No log 1.0 7 2.7061 0.5 0.2790 0.5 0.001

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.2
  • Tokenizers 0.19.1