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

# frozen_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: 0.7314
- Accuracy: 0.7793
- F1: 0.7753
- Precision: 0.7785
- Recall: 0.7793

## 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: 1e-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: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8422        | 1.0   | 3596  | 0.8104          | 0.7681   | 0.7632 | 0.7669    | 0.7681 |
| 0.7923        | 2.0   | 7192  | 0.7738          | 0.7711   | 0.7666 | 0.7700    | 0.7711 |
| 0.7597        | 3.0   | 10788 | 0.7485          | 0.7754   | 0.7716 | 0.7741    | 0.7754 |
| 0.7564        | 4.0   | 14384 | 0.7314          | 0.7793   | 0.7753 | 0.7785    | 0.7793 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1