Agreeableness_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: 0.1612
• Rmse: 0.4014
• Mae: 0.3742
• Corr: 0.3925

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	0.2366	0.4865	0.4640	0.3374
No log	2.0	2	0.1854	0.4306	0.4052	0.3994
No log	3.0	3	0.1612	0.4014	0.3742	0.3925

Framework versions

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