| --- |
| license: apache-2.0 |
| base_model: sentence-transformers/all-mpnet-base-v2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: IKT_classifier_mitigation_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_mitigation_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: 0.6517 |
| - Precision Micro: 0.3667 |
| - Precision Weighted: 0.4273 |
| - Precision Samples: 0.4539 |
| - Recall Micro: 0.7543 |
| - Recall Weighted: 0.7543 |
| - Recall Samples: 0.7982 |
| - F1-score: 0.5422 |
| - Accuracy: 0.1654 |
| |
| ## 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: 3.6181464293180716e-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: 300.0 |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:|:--------:| |
| | No log | 1.0 | 398 | 1.0635 | 0.1718 | 0.2238 | 0.1763 | 0.7714 | 0.7714 | 0.7945 | 0.2794 | 0.0 | |
| | 1.2442 | 2.0 | 796 | 0.8827 | 0.2167 | 0.2522 | 0.2388 | 0.7543 | 0.7543 | 0.7863 | 0.3518 | 0.0 | |
| | 0.9539 | 3.0 | 1194 | 0.7579 | 0.2710 | 0.3279 | 0.2979 | 0.7543 | 0.7543 | 0.7932 | 0.4134 | 0.0150 | |
| | 0.8265 | 4.0 | 1592 | 0.6773 | 0.3377 | 0.3943 | 0.3937 | 0.7429 | 0.7429 | 0.7901 | 0.4961 | 0.0752 | |
| | 0.8265 | 5.0 | 1990 | 0.6517 | 0.3667 | 0.4273 | 0.4539 | 0.7543 | 0.7543 | 0.7982 | 0.5422 | 0.1654 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
