metadata
library_name: transformers
language:
- multilingual
- bn
- cs
- de
- en
- et
- fi
- fr
- gu
- ha
- hi
- is
- ja
- kk
- km
- lt
- lv
- pl
- ps
- ru
- ta
- tr
- uk
- xh
- zh
- zu
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- quality-estimation
- regression
- generated_from_trainer
datasets:
- ymoslem/wmt-da-human-evaluation
model-index:
- name: Quality Estimation for Machine Translation
results: []
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: 0.0561
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: 0.0003
- 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 |
|---|---|---|---|
| 0.0656 | 0.1004 | 1000 | 0.0636 |
| 0.0643 | 0.2007 | 2000 | 0.0623 |
| 0.0592 | 0.3011 | 3000 | 0.0598 |
| 0.0596 | 0.4015 | 4000 | 0.0586 |
| 0.0575 | 0.5019 | 5000 | 0.0577 |
| 0.0574 | 0.6022 | 6000 | 0.0570 |
| 0.0584 | 0.7026 | 7000 | 0.0566 |
| 0.0574 | 0.8030 | 8000 | 0.0563 |
| 0.0565 | 0.9033 | 9000 | 0.0561 |
| 0.0557 | 1.0037 | 10000 | 0.0561 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0