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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/convnextv2-tiny-1k-224
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: convnextv2-tiny-1k-224-finetuned-barkley
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results: []
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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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# convnextv2-tiny-1k-224-finetuned-barkley
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This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co./facebook/convnextv2-tiny-1k-224) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0083
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- Precision: 1.0
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- Recall: 1.0
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- F1: 1.0
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- Accuracy: 1.0
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- Top1 Accuracy: 1.0
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- Error Rate: 0.0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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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: 0.1
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- num_epochs: 30
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Top1 Accuracy | Error Rate |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
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| 1.4696 | 1.0 | 38 | 1.1807 | 0.7273 | 0.6513 | 0.6180 | 0.6768 | 0.6513 | 0.3232 |
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| 0.7197 | 2.0 | 76 | 0.3719 | 0.9439 | 0.9408 | 0.9404 | 0.9434 | 0.9474 | 0.0566 |
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| 0.2388 | 3.0 | 114 | 0.1489 | 0.9688 | 0.9671 | 0.9671 | 0.9716 | 0.9671 | 0.0284 |
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| 0.1048 | 4.0 | 152 | 0.0730 | 0.9868 | 0.9868 | 0.9868 | 0.9878 | 0.9868 | 0.0122 |
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| 0.1103 | 5.0 | 190 | 0.0288 | 0.9868 | 0.9868 | 0.9868 | 0.9878 | 0.9868 | 0.0122 |
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| 0.072 | 6.0 | 228 | 0.0537 | 0.9877 | 0.9868 | 0.9869 | 0.9868 | 0.9868 | 0.0132 |
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| 0.0248 | 7.0 | 266 | 0.0083 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
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| 0.0371 | 8.0 | 304 | 0.0653 | 0.9819 | 0.9803 | 0.9802 | 0.9800 | 0.9803 | 0.0200 |
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| 0.0626 | 9.0 | 342 | 0.2271 | 0.9545 | 0.9408 | 0.9404 | 0.95 | 0.9408 | 0.0500 |
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| 0.07 | 10.0 | 380 | 0.0304 | 0.9936 | 0.9934 | 0.9934 | 0.9933 | 0.9934 | 0.0067 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.3.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.19.1
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