---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-stance
  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. -->

# roberta-stance

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1034
- Accuracy: 0.6232
- Precision: 0.6077
- Recall: 0.6301
- F1: 0.6127

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 46   | 1.0695          | 0.5184   | 0.1728    | 0.3333 | 0.2276 |
| No log        | 2.0   | 92   | 1.0372          | 0.5184   | 0.1728    | 0.3333 | 0.2276 |
| No log        | 3.0   | 138  | 0.9757          | 0.5746   | 0.4121    | 0.4214 | 0.3711 |
| No log        | 4.0   | 184  | 0.8826          | 0.6063   | 0.5820    | 0.5298 | 0.5423 |
| No log        | 5.0   | 230  | 0.8429          | 0.6166   | 0.6159    | 0.6011 | 0.5824 |
| No log        | 6.0   | 276  | 0.8153          | 0.6472   | 0.6257    | 0.6376 | 0.6294 |
| No log        | 7.0   | 322  | 0.8600          | 0.6559   | 0.6492    | 0.6427 | 0.6315 |
| No log        | 8.0   | 368  | 0.8912          | 0.6299   | 0.6138    | 0.6159 | 0.6108 |
| No log        | 9.0   | 414  | 1.0091          | 0.6161   | 0.6048    | 0.6345 | 0.6084 |
| No log        | 10.0  | 460  | 1.1034          | 0.6232   | 0.6077    | 0.6301 | 0.6127 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0