| --- |
| 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: 1.0515 |
| - Precision Micro: 0.2570 |
| - Precision Weighted: 0.2809 |
| - Precision Samples: 0.2896 |
| - Recall Micro: 0.6815 |
| - Recall Weighted: 0.6815 |
| - Recall Samples: 0.7119 |
| - F1-score: 0.3907 |
| - Accuracy: 0.0095 |
| |
| ## 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 | 313 | 1.2909 | 0.1858 | 0.2078 | 0.1957 | 0.7185 | 0.7185 | 0.7222 | 0.2977 | 0.0 | |
| | 1.262 | 2.0 | 626 | 1.0875 | 0.2099 | 0.2605 | 0.2295 | 0.7852 | 0.7852 | 0.8071 | 0.3431 | 0.0 | |
| | 1.262 | 3.0 | 939 | 1.0171 | 0.2284 | 0.2612 | 0.2539 | 0.7630 | 0.7630 | 0.7746 | 0.3643 | 0.0095 | |
| | 1.0059 | 4.0 | 1252 | 1.0510 | 0.2519 | 0.2764 | 0.2914 | 0.7259 | 0.7259 | 0.7563 | 0.4013 | 0.0095 | |
| | 0.8421 | 5.0 | 1565 | 1.0515 | 0.2570 | 0.2809 | 0.2896 | 0.6815 | 0.6815 | 0.7119 | 0.3907 | 0.0095 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
