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

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: 1.9419
- Accuracy: 0.6933
- Macro Precision: 0.6604
- Macro F1: 0.6503

## 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  | 1.5639          | 0.41     | 0.4728          | 0.3904   |
| No log        | 2.0   | 232  | 1.1501          | 0.5833   | 0.5591          | 0.5659   |
| No log        | 3.0   | 348  | 1.1315          | 0.64     | 0.6182          | 0.6220   |
| No log        | 4.0   | 464  | 1.2345          | 0.67     | 0.6471          | 0.6237   |
| 0.9897        | 5.0   | 580  | 1.3952          | 0.62     | 0.5912          | 0.5960   |
| 0.9897        | 6.0   | 696  | 1.5032          | 0.68     | 0.6370          | 0.6407   |
| 0.9897        | 7.0   | 812  | 1.6859          | 0.6833   | 0.6437          | 0.6478   |
| 0.9897        | 8.0   | 928  | 1.9130          | 0.69     | 0.6638          | 0.6393   |
| 0.0959        | 9.0   | 1044 | 1.9246          | 0.68     | 0.6526          | 0.6459   |
| 0.0959        | 10.0  | 1160 | 1.8800          | 0.6867   | 0.6378          | 0.6392   |
| 0.0959        | 11.0  | 1276 | 1.9436          | 0.69     | 0.6623          | 0.6519   |
| 0.0959        | 12.0  | 1392 | 1.9419          | 0.6933   | 0.6604          | 0.6503   |


### Framework versions

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