---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: stance_class_l
  results: []
---

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# stance_class_l

This model is a fine-tuned version of vinai/bertweet-base on the dataset of 804 labeled tweets on the cancer risk controversy of Roundup Weedkiller \. 
It classified the stance of an individual's tweet toward Bayer, Monsanto, or other relevant organizations in the crisis. 
Two stances are classified: (0) Aggressive, (1) Non-Aggressive (neutral and accommodative).
It achieves the following results on the evaluation set:
- Loss: 0.6084
- Accuracy: 0.8447

## 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: 2.924e-05
- train_batch_size: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3566        | 1.0   | 17   | 0.4855          | 0.7578   |
| 0.2532        | 2.0   | 34   | 0.3632          | 0.8509   |
| 0.2351        | 3.0   | 51   | 0.3773          | 0.8509   |
| 0.043         | 4.0   | 68   | 0.3553          | 0.8571   |
| 0.08          | 5.0   | 85   | 0.4682          | 0.8447   |
| 0.3089        | 6.0   | 102  | 0.4686          | 0.8509   |
| 0.035         | 7.0   | 119  | 0.5876          | 0.8323   |
| 0.0188        | 8.0   | 136  | 0.5469          | 0.8571   |
| 0.021         | 9.0   | 153  | 0.5022          | 0.8447   |
| 0.0533        | 10.0  | 170  | 0.5240          | 0.8385   |
| 0.0175        | 11.0  | 187  | 0.6352          | 0.8447   |
| 0.0106        | 12.0  | 204  | 0.5856          | 0.8447   |
| 1.9534        | 13.0  | 221  | 0.5938          | 0.8509   |
| 0.0143        | 14.0  | 238  | 0.6074          | 0.8447   |
| 0.0079        | 15.0  | 255  | 0.6084          | 0.8447   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.2