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---
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
- generated_from_trainer
datasets:
- ymoslem/wmt-da-human-evaluation
model-index:
- name: Quality Estimation for Machine Translation
results: []
pipeline_tag: text-classification
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Quality Estimation for Machine Translation
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/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 |