xlmr-en-de-train_shuffled-1986-test2000

This model is a fine-tuned version of xlm-roberta-base on the wmt20_mlqe_task1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5216
• R Squared: 0.0640
• Mae: 0.5363
• Pearson R: 0.4009

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	375	0.5588	-0.0028	0.5813	0.3172
0.6965	2.0	750	0.5465	0.0193	0.5548	0.3819
0.6808	3.0	1125	0.5216	0.0640	0.5363	0.4009

Framework versions

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