metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-cpp
results: []
roberta-base-cpp
This model is a fine-tuned version of 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