xlmr-si-en-all_shuffled-1986-test1000

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

• Loss: 0.7301
• R Squared: 0.1215
• Mae: 0.6851
• Pearson R: 0.5063

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: 16
• eval_batch_size: 16
• seed: 1986
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	R Squared	Mae	Pearson R
No log	1.0	438	0.6913	0.1682	0.7202	0.4227
0.78	2.0	876	0.6490	0.2191	0.6692	0.5122
0.6387	3.0	1314	0.7301	0.1215	0.6851	0.5063

Framework versions

• Transformers 4.34.1
• Pytorch 2.0.1+cu117
• Datasets 2.14.6
• Tokenizers 0.14.1