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---
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
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