---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: IKT_classifier_economywide_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_economywide_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: 0.1642
- Precision Weighted: 0.9530
- Precision Macro: 0.9524
- Recall Weighted: 0.9528
- Recall Samples: 0.9532
- F1-score: 0.9527
- Accuracy: 0.9528

## 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: 9.375102561418467e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100.0
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision Weighted | Precision Macro | Recall Weighted | Recall Samples | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:---------------:|:--------------:|:--------:|:--------:|
| No log        | 1.0   | 30   | 0.3847          | 0.9356             | 0.9340          | 0.9340          | 0.9354         | 0.9339   | 0.9340   |
| No log        | 2.0   | 60   | 0.3545          | 0.8911             | 0.8933          | 0.8868          | 0.8832         | 0.8853   | 0.8868   |
| No log        | 3.0   | 90   | 0.1387          | 0.9623             | 0.9621          | 0.9623          | 0.9621         | 0.9621   | 0.9623   |
| No log        | 4.0   | 120  | 0.1840          | 0.9541             | 0.9555          | 0.9528          | 0.9511         | 0.9525   | 0.9528   |
| No log        | 5.0   | 150  | 0.1642          | 0.9530             | 0.9524          | 0.9528          | 0.9532         | 0.9527   | 0.9528   |


### Framework versions

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