---
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   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3