Quality Estimation for Machine Translation
This model is a fine-tuned version of answerdotai/ModernBERT-large on the ymoslem/wmt-da-human-evaluation dataset. It achieves the following results on the evaluation set:
- Loss: 0.0564
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: 8e-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 |
|---|---|---|---|
| 0.0631 | 0.1004 | 1000 | 0.0674 |
| 0.0614 | 0.2007 | 2000 | 0.0599 |
| 0.0578 | 0.3011 | 3000 | 0.0585 |
| 0.0585 | 0.4015 | 4000 | 0.0579 |
| 0.0568 | 0.5019 | 5000 | 0.0570 |
| 0.057 | 0.6022 | 6000 | 0.0568 |
| 0.0579 | 0.7026 | 7000 | 0.0567 |
| 0.0573 | 0.8030 | 8000 | 0.0565 |
| 0.0568 | 0.9033 | 9000 | 0.0564 |
| 0.0571 | 1.0037 | 10000 | 0.0564 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
answerdotai/ModernBERT-large