---
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: 0.0844
- Accuracy: 0.9550

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1085        | 0.05  | 1000  | 0.1080          | 0.9183   |
| 0.0716        | 0.1   | 2000  | 0.2524          | 0.8473   |
| 0.0615        | 0.15  | 3000  | 0.1182          | 0.9299   |
| 0.0648        | 0.2   | 4000  | 0.0757          | 0.9498   |
| 0.0522        | 0.25  | 5000  | 0.1201          | 0.9273   |
| 0.0377        | 0.3   | 6000  | 0.0846          | 0.9555   |
| 0.0447        | 0.35  | 7000  | 0.1036          | 0.9323   |
| 0.0421        | 0.4   | 8000  | 0.1804          | 0.8914   |
| 0.0364        | 0.45  | 9000  | 0.0494          | 0.9628   |
| 0.0301        | 0.5   | 10000 | 0.0583          | 0.9689   |
| 0.0281        | 0.55  | 11000 | 0.0554          | 0.9689   |
| 0.0362        | 0.6   | 12000 | 0.0898          | 0.9428   |
| 0.022         | 0.65  | 13000 | 0.0772          | 0.9687   |
| 0.0221        | 0.7   | 14000 | 0.0706          | 0.9613   |
| 0.0256        | 0.75  | 15000 | 0.0487          | 0.9719   |
| 0.0215        | 0.8   | 16000 | 0.0427          | 0.9765   |
| 0.0162        | 0.85  | 17000 | 0.0437          | 0.9742   |
| 0.0186        | 0.9   | 18000 | 0.0613          | 0.9680   |
| 0.0211        | 0.95  | 19000 | 0.0950          | 0.9514   |
| 0.0136        | 1.0   | 20000 | 0.0844          | 0.9550   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.8.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1