---
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