---
license: apache-2.0
base_model: sentence-transformers/LaBSE
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: news_classifier_ft
  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. -->

# news_classifier_ft

This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3820
- Accuracy: 0.9029
- F1: 0.9025
- Precision: 0.9030
- Recall: 0.9029

## 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: 2e-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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3544        | 1.0   | 3596  | 0.3517          | 0.8861   | 0.8860 | 0.8915    | 0.8861 |
| 0.2738        | 2.0   | 7192  | 0.3190          | 0.8995   | 0.8987 | 0.9025    | 0.8995 |
| 0.19          | 3.0   | 10788 | 0.3524          | 0.9016   | 0.9015 | 0.9019    | 0.9016 |
| 0.1402        | 4.0   | 14384 | 0.3820          | 0.9029   | 0.9025 | 0.9030    | 0.9029 |
| 0.1055        | 5.0   | 17980 | 0.4399          | 0.9022   | 0.9018 | 0.9024    | 0.9022 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1