Conscientiousness_continuous

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1768
  • Rmse: 0.4205
  • Mae: 0.3569
  • Corr: -0.4410

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Use 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: 3

Training results

Training Loss Epoch Step Validation Loss Rmse Mae Corr
No log 1.0 1 0.2352 0.4850 0.4016 -0.6156
No log 2.0 2 0.1947 0.4413 0.3720 -0.4594
No log 3.0 3 0.1768 0.4205 0.3569 -0.4410

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.4.0
  • Datasets 2.20.0
  • Tokenizers 0.21.1
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