---
base_model: nghuyong/ernie-1.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Ernie-PoliticalBias-Finetune
  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. -->

# Ernie-PoliticalBias-Finetune

This model is a fine-tuned version of [nghuyong/ernie-1.0](https://huggingface.co/nghuyong/ernie-1.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4782
- Accuracy: 0.8021
- F1: 0.7908
- Precision: 0.8155
- Recall: 0.7776

## 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: 5e-05
- train_batch_size: 8
- 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.587         | 1.0   | 3845  | 0.5531          | 0.7607   | 0.7532 | 0.7679    | 0.7454 |
| 0.7662        | 2.0   | 7690  | 0.5028          | 0.7948   | 0.7839 | 0.8301    | 0.7626 |
| 0.4928        | 3.0   | 11535 | 0.4782          | 0.8021   | 0.7908 | 0.8155    | 0.7776 |
| 0.414         | 4.0   | 15380 | 0.5139          | 0.8179   | 0.8043 | 0.8335    | 0.7878 |
| 0.2473        | 5.0   | 19225 | 0.5511          | 0.8218   | 0.8103 | 0.8193    | 0.8033 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1