ymoslem/ModernBERT-base-qe-lr5e-05-v1

Quality Estimation for Machine Translation

This model is a fine-tuned version of answerdotai/ModernBERT-base on the ymoslem/wmt-da-human-evaluation dataset. It achieves the following results on the evaluation set:

• Loss: 0.0632

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: 5e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• training_steps: 10000

Training results

Training Loss	Epoch	Step	Validation Loss
0.0671	0.1004	1000	0.0665
0.067	0.2007	2000	0.0652
0.064	0.3011	3000	0.0644
0.0641	0.4015	4000	0.0638
0.0629	0.5019	5000	0.0635
0.0637	0.6022	6000	0.0634
0.0653	0.7026	7000	0.0633
0.0644	0.8030	8000	0.0633
0.0638	0.9033	9000	0.0633
0.064	1.0037	10000	0.0632

Framework versions

• Transformers 4.48.0
• Pytorch 2.4.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0