---
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