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README.md ADDED
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+ ---
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+ base_model: Kevinger/setfit-hub-report
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: Hub-Repoop-1706130115
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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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+ # Hub-Repoop-1706130115
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+
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+ This model is a fine-tuned version of [Kevinger/setfit-hub-report](https://huggingface.co/Kevinger/setfit-hub-report) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1746
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+ - F1: 0.7727
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+ - Roc Auc: 0.8666
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+ - Accuracy: 0.7637
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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: 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: linear
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+ - num_epochs: 13
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 277 | 0.3104 | 0.0 | 0.5 | 0.0 |
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+ | 0.3599 | 2.0 | 554 | 0.2312 | 0.5624 | 0.7027 | 0.4135 |
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+ | 0.3599 | 3.0 | 831 | 0.1897 | 0.7479 | 0.8275 | 0.6730 |
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+ | 0.2035 | 4.0 | 1108 | 0.1768 | 0.7645 | 0.8546 | 0.7363 |
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+ | 0.2035 | 5.0 | 1385 | 0.1760 | 0.7649 | 0.8579 | 0.7447 |
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+ | 0.1422 | 6.0 | 1662 | 0.1788 | 0.7559 | 0.8562 | 0.7447 |
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+ | 0.1422 | 7.0 | 1939 | 0.1766 | 0.7633 | 0.8617 | 0.7553 |
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+ | 0.1096 | 8.0 | 2216 | 0.1746 | 0.7727 | 0.8666 | 0.7637 |
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+ | 0.1096 | 9.0 | 2493 | 0.1891 | 0.7457 | 0.8511 | 0.7363 |
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+ | 0.0891 | 10.0 | 2770 | 0.1855 | 0.7524 | 0.8540 | 0.7405 |
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+ | 0.0769 | 11.0 | 3047 | 0.1824 | 0.7655 | 0.8629 | 0.7574 |
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+ | 0.0769 | 12.0 | 3324 | 0.1835 | 0.7655 | 0.8629 | 0.7532 |
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+ | 0.0706 | 13.0 | 3601 | 0.1867 | 0.7604 | 0.8603 | 0.7511 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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