---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base_LOGIC_Native
  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-base_LOGIC_Native

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1872
- Accuracy: 0.6367
- Macro Precision: 0.6085
- Macro F1: 0.5927

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:--------:|
| No log        | 1.0   | 116  | 2.2572          | 0.3633   | 0.3744          | 0.3280   |
| No log        | 2.0   | 232  | 1.6881          | 0.4933   | 0.4444          | 0.4351   |
| No log        | 3.0   | 348  | 1.5136          | 0.5767   | 0.5515          | 0.5475   |
| No log        | 4.0   | 464  | 1.5064          | 0.6033   | 0.5808          | 0.5616   |
| 1.4911        | 5.0   | 580  | 1.5690          | 0.5967   | 0.5912          | 0.5609   |
| 1.4911        | 6.0   | 696  | 1.5927          | 0.6267   | 0.6002          | 0.5907   |
| 1.4911        | 7.0   | 812  | 1.6903          | 0.6267   | 0.5964          | 0.5876   |
| 1.4911        | 8.0   | 928  | 1.8527          | 0.6167   | 0.5924          | 0.5848   |
| 0.2082        | 9.0   | 1044 | 2.0450          | 0.6267   | 0.6208          | 0.5933   |
| 0.2082        | 10.0  | 1160 | 2.0799          | 0.63     | 0.5922          | 0.5852   |
| 0.2082        | 11.0  | 1276 | 2.1676          | 0.6333   | 0.6069          | 0.5889   |
| 0.2082        | 12.0  | 1392 | 2.1872          | 0.6367   | 0.6085          | 0.5927   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2