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Domain-specific continued pretraining of RoBERTa
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metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
model-index:
  - name: roberta-continued-pretraining
    results: []

roberta-continued-pretraining

This model is a fine-tuned version of 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