CHAR_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: 0.0962
• Rmse: 0.3102
• Mae: 0.2666
• Corr: -0.1535

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	0.1521	0.3900	0.3554	-0.2495
No log	2.0	2	0.1133	0.3365	0.2961	-0.1164
No log	3.0	3	0.0962	0.3102	0.2666	-0.1535

Framework versions

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