xlmr-en-de-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: 0.6765
• R Squared: 0.0251
• Mae: 0.4855
• Pearson R: 0.1748

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	0.6958	-0.0027	0.5213	0.1392
0.6567	2.0	876	0.6811	0.0185	0.4889	0.1460
0.6332	3.0	1314	0.6765	0.0251	0.4855	0.1748

Framework versions

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