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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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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: windowz_test |
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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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# windowz_test |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Model Preparation Time: 0.001 |
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- Accuracy: 0.9678 |
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- F1: 0.9630 |
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- Iou: 0.9377 |
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- Loss: 0.1675 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Model Preparation Time | | Validation Loss | |
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|:-------------:|:------:|:----:|:----------------------:|:------:|:---------------:| |
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| 1.0939 | 0.0501 | 257 | 0.001 | 0.5935 | 1.0369 | |
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| 1.0201 | 0.1003 | 514 | 0.001 | 0.6796 | 0.9606 | |
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| 0.9555 | 0.1504 | 771 | 0.001 | 0.7692 | 0.8134 | |
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| 0.8988 | 0.2005 | 1028 | 0.001 | 0.8883 | 0.4634 | |
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| 0.8663 | 0.2507 | 1285 | 0.001 | 0.9029 | 0.3463 | |
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| 0.8516 | 0.3008 | 1542 | 0.001 | 0.8728 | 0.3075 | |
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| 0.7798 | 0.3510 | 1799 | 0.001 | 0.9528 | 0.7747 | |
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| 0.7601 | 0.4011 | 2056 | 0.001 | 0.8082 | 0.5655 | |
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| 0.7723 | 0.4512 | 2313 | 0.001 | 0.9550 | 0.3013 | |
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| 0.7258 | 0.5014 | 2570 | 0.001 | 0.9673 | 0.1914 | |
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| 0.7085 | 0.5515 | 2827 | 0.001 | 0.9377 | 0.1675 | |
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| 0.7058 | 0.6016 | 3084 | 0.001 | 0.9406 | 0.2294 | |
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| 0.7008 | 0.6518 | 3341 | 0.001 | 0.9189 | 0.2342 | |
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| 0.6691 | 0.7019 | 3598 | 0.001 | 0.9404 | 0.2161 | |
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### Framework versions |
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- Transformers 4.45.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.3 |
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