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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: weed_hybrid_transformer |
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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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# weed_hybrid_transformer |
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This model is a fine-tuned version of [](https://huggingface.co/) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1026 |
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- Accuracy: 0.9667 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 8.3274 | 1.0 | 150 | 0.8170 | 0.8233 | |
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| 2.734 | 2.0 | 300 | 0.3290 | 0.9 | |
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| 2.6813 | 3.0 | 450 | 0.2720 | 0.9167 | |
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| 1.7794 | 4.0 | 600 | 0.2369 | 0.9067 | |
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| 1.6344 | 5.0 | 750 | 0.1589 | 0.9567 | |
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| 1.394 | 6.0 | 900 | 0.1484 | 0.9533 | |
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| 1.2546 | 7.0 | 1050 | 0.1382 | 0.9567 | |
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| 1.2253 | 8.0 | 1200 | 0.1565 | 0.9567 | |
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| 0.7844 | 9.0 | 1350 | 0.1721 | 0.9433 | |
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| 0.4964 | 10.0 | 1500 | 0.1026 | 0.9667 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.5.0+cu124 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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