---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-continued-pretraining
  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-continued-pretraining

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: 1.2371

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6688        | 0.3337 | 1000 | 1.4834          |
| 1.5534        | 0.6673 | 2000 | 1.4207          |
| 1.5071        | 1.0010 | 3000 | 1.3937          |
| 1.4337        | 1.3347 | 4000 | 1.3301          |
| 1.4162        | 1.6683 | 5000 | 1.3126          |
| 1.372         | 2.0020 | 6000 | 1.2803          |
| 1.3325        | 2.3357 | 7000 | 1.2564          |
| 1.307         | 2.6693 | 8000 | 1.2371          |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0