---
license: apache-2.0
base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mpnet-multi-agri-classifier
  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. -->

# mpnet-multi-agri-classifier

This model is a fine-tuned version of [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3444
- Precision Macro: 0.8402
- Precision Weighted: 0.9196
- Recall Macro: 0.9042
- Recall Weighted: 0.9046
- F1-score: 0.8655
- Accuracy: 0.9046

## 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: 6.9e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
| 0.393         | 1.0   | 334  | 0.2938          | 0.8528          | 0.9132             | 0.8773       | 0.9092          | 0.8641   | 0.9092   |
| 0.3213        | 2.0   | 668  | 0.3049          | 0.8299          | 0.9110             | 0.8885       | 0.8966          | 0.8534   | 0.8966   |
| 0.2591        | 3.0   | 1002 | 0.2561          | 0.8654          | 0.9226             | 0.8937       | 0.9184          | 0.8784   | 0.9184   |
| 0.1853        | 4.0   | 1336 | 0.3254          | 0.8386          | 0.9190             | 0.9034       | 0.9034          | 0.8641   | 0.9034   |
| 0.1119        | 5.0   | 1670 | 0.3444          | 0.8402          | 0.9196             | 0.9042       | 0.9046          | 0.8655   | 0.9046   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.15.0