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--- |
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library_name: transformers |
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language: |
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- multilingual |
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- bn |
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- cs |
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- de |
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- en |
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- et |
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- fi |
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- fr |
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- gu |
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- ha |
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- hi |
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- is |
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- ja |
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- kk |
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- km |
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- lt |
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- lv |
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- pl |
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- ps |
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- ru |
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- ta |
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- tr |
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- uk |
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- xh |
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- zh |
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- zu |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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tags: |
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- quality-estimation |
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- regression |
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- generated_from_trainer |
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datasets: |
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- ymoslem/wmt-da-human-evaluation |
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model-index: |
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- name: Quality Estimation for Machine Translation |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Quality Estimation for Machine Translation |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0561 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.0656 | 0.1004 | 1000 | 0.0636 | |
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| 0.0643 | 0.2007 | 2000 | 0.0623 | |
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| 0.0592 | 0.3011 | 3000 | 0.0598 | |
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| 0.0596 | 0.4015 | 4000 | 0.0586 | |
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| 0.0575 | 0.5019 | 5000 | 0.0577 | |
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| 0.0574 | 0.6022 | 6000 | 0.0570 | |
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| 0.0584 | 0.7026 | 7000 | 0.0566 | |
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| 0.0574 | 0.8030 | 8000 | 0.0563 | |
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| 0.0565 | 0.9033 | 9000 | 0.0561 | |
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| 0.0557 | 1.0037 | 10000 | 0.0561 | |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.4.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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