|
--- |
|
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 |
