---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MSPoliBERT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MSPoliBERT

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on tnwei/ms-newspapers dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3062
- Accuracy: 0.9310

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Label Mappings
- 0: Economic Concerns
- 1: Racial discrimination or polarization
- 2: Leadership weaknesses
- 3: Development and infrastructure gaps
- 4: Corruption
- 5: Political instablility
- 6: Socials and Public safety
- 7: Administration
- 8: Education
- 9: Religion issues
- 10: Environmental
- 11: Others

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3888        | 1.0   | 1138 | 0.3691          | 0.9178   |
| 0.2981        | 2.0   | 2276 | 0.3425          | 0.9240   |
| 0.2073        | 3.0   | 3414 | 0.3062          | 0.9310   |
| 0.1642        | 4.0   | 4552 | 0.3301          | 0.9336   |
| 0.1175        | 5.0   | 5690 | 0.3387          | 0.9345   |
| 0.1201        | 6.0   | 6828 | 0.3298          | 0.9358   |
| 0.1078        | 7.0   | 7966 | 0.3751          | 0.9327   |
| 0.0945        | 8.0   | 9104 | 0.3503          | 0.9349   |


### Framework versions

- Transformers 4.18.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.12.1