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metadata
license: apache-2.0
base_model: facebook/dinov2-small
tags:
  - image-classification
  - vision
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: dinov2-small-types-of-film-shots-vN
    results: []

dinov2-small-types-of-film-shots-vN

This model is a fine-tuned version of facebook/dinov2-small on the szymonrucinski/types-of-film-shots dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9864
  • Accuracy: 0.6259

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: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 17480
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 12.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.6177 0.97 24 1.5501 0.4101
1.3029 1.99 49 1.2448 0.5108
1.1785 2.96 73 1.0556 0.5252
1.2146 3.98 98 1.2316 0.5396
0.8389 4.99 123 1.0235 0.5971
0.7883 5.97 147 0.9960 0.6259
0.7899 6.98 172 1.1354 0.5540
0.663 8.0 197 1.0971 0.5827
0.6013 8.97 221 0.9864 0.6259
0.6276 9.99 246 1.0182 0.6115
0.5196 10.96 270 1.0074 0.6547
0.4761 11.7 288 0.9956 0.6763

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2