| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: IKT_classifier_netzero_best |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # IKT_classifier_netzero_best |
| |
| 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. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9526 |
| - Precision Macro: 0.7813 |
| - Precision Weighted: 0.8164 |
| - Recall Macro: 0.7734 |
| - Recall Weighted: 0.7812 |
| - F1-score: 0.7644 |
| - Accuracy: 0.7812 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 9.588722322096848e-05 |
| - train_batch_size: 3 |
| - eval_batch_size: 3 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 400.0 |
| - num_epochs: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:| |
| | No log | 1.0 | 114 | 0.8267 | 0.8056 | 0.8151 | 0.6601 | 0.6875 | 0.6418 | 0.6875 | |
| | No log | 2.0 | 228 | 0.4916 | 0.8095 | 0.8371 | 0.8290 | 0.8125 | 0.8113 | 0.8125 | |
| | No log | 3.0 | 342 | 0.4784 | 0.8535 | 0.8920 | 0.8682 | 0.875 | 0.8569 | 0.875 | |
| | No log | 4.0 | 456 | 0.8909 | 0.7813 | 0.8164 | 0.7734 | 0.7812 | 0.7644 | 0.7812 | |
| | 0.6167 | 5.0 | 570 | 0.6673 | 0.8242 | 0.8650 | 0.8649 | 0.8125 | 0.8260 | 0.8125 | |
| | 0.6167 | 6.0 | 684 | 0.7110 | 0.8413 | 0.8795 | 0.8845 | 0.8438 | 0.8505 | 0.8438 | |
| | 0.6167 | 7.0 | 798 | 1.3731 | 0.7778 | 0.8281 | 0.7702 | 0.7188 | 0.7380 | 0.7188 | |
| | 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 |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
