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

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1043
- Accuracy: 0.9419

## 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: 2
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1244        | 0.125 | 1000 | 0.0842          | 0.931    |
| 0.0851        | 0.25  | 2000 | 0.2041          | 0.7715   |
| 0.0632        | 0.375 | 3000 | 0.1610          | 0.9123   |
| 0.0521        | 0.5   | 4000 | 0.0907          | 0.9224   |
| 0.0426        | 0.625 | 5000 | 0.2447          | 0.8784   |
| 0.0341        | 0.75  | 6000 | 0.0667          | 0.9641   |
| 0.0252        | 0.875 | 7000 | 0.0872          | 0.957    |
| 0.0184        | 1.0   | 8000 | 0.1043          | 0.9419   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1