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README.md
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---
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license: apache-2.0
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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: IKT_classifier_netzero_best
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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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# IKT_classifier_netzero_best
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This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9526
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- Precision Macro: 0.7813
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- Precision Weighted: 0.8164
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- Recall Macro: 0.7734
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- Recall Weighted: 0.7812
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- F1-score: 0.7644
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- Accuracy: 0.7812
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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: 9.588722322096848e-05
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- train_batch_size: 3
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- eval_batch_size: 3
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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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- lr_scheduler_warmup_steps: 400.0
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- num_epochs: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
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| No log | 1.0 | 114 | 0.8267 | 0.8056 | 0.8151 | 0.6601 | 0.6875 | 0.6418 | 0.6875 |
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| No log | 2.0 | 228 | 0.4916 | 0.8095 | 0.8371 | 0.8290 | 0.8125 | 0.8113 | 0.8125 |
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| No log | 3.0 | 342 | 0.4784 | 0.8535 | 0.8920 | 0.8682 | 0.875 | 0.8569 | 0.875 |
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| No log | 4.0 | 456 | 0.8909 | 0.7813 | 0.8164 | 0.7734 | 0.7812 | 0.7644 | 0.7812 |
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| 0.6167 | 5.0 | 570 | 0.6673 | 0.8242 | 0.8650 | 0.8649 | 0.8125 | 0.8260 | 0.8125 |
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| 0.6167 | 6.0 | 684 | 0.7110 | 0.8413 | 0.8795 | 0.8845 | 0.8438 | 0.8505 | 0.8438 |
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| 0.6167 | 7.0 | 798 | 1.3731 | 0.7778 | 0.8281 | 0.7702 | 0.7188 | 0.7380 | 0.7188 |
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| 0.6167 | 8.0 | 912 | 0.9526 | 0.7813 | 0.8164 | 0.7734 | 0.7812 | 0.7644 | 0.7812 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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