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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/dinov2-small
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: dinov2-small-types-of-film-shots-vN
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+ results: []
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+ ---
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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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+
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+ # dinov2-small-types-of-film-shots-vN
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+
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+ This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9956
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+ - Accuracy: 0.6763
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 17480
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 32
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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: 0.05
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+ - num_epochs: 12.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.6177 | 0.97 | 24 | 1.5501 | 0.4101 |
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+ | 1.3029 | 1.99 | 49 | 1.2448 | 0.5108 |
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+ | 1.1785 | 2.96 | 73 | 1.0556 | 0.5252 |
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+ | 1.2146 | 3.98 | 98 | 1.2316 | 0.5396 |
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+ | 0.8389 | 4.99 | 123 | 1.0235 | 0.5971 |
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+ | 0.7883 | 5.97 | 147 | 0.9960 | 0.6259 |
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+ | 0.7899 | 6.98 | 172 | 1.1354 | 0.5540 |
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+ | 0.663 | 8.0 | 197 | 1.0971 | 0.5827 |
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+ | 0.6013 | 8.97 | 221 | 0.9864 | 0.6259 |
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+ | 0.6276 | 9.99 | 246 | 1.0182 | 0.6115 |
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+ | 0.5196 | 10.96 | 270 | 1.0074 | 0.6547 |
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+ | 0.4761 | 11.7 | 288 | 0.9956 | 0.6763 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.0.dev0
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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