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---
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
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