MT Quality Estimation
Collection
Models for reference-free quality estimation of machine translation
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8 items
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Updated
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1
roberta-base-qe-v1
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0626
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 |
|---|---|---|---|
| 0.063 | 0.1004 | 1000 | 0.0816 |
| 0.062 | 0.2007 | 2000 | 0.0667 |
| 0.0582 | 0.3011 | 3000 | 0.0622 |
| 0.0589 | 0.4015 | 4000 | 0.0604 |
| 0.0576 | 0.5019 | 5000 | 0.0591 |
| 0.0577 | 0.6022 | 6000 | 0.0597 |
| 0.0581 | 0.7026 | 7000 | 0.0649 |
| 0.0582 | 0.8030 | 8000 | 0.0624 |
| 0.0569 | 0.9033 | 9000 | 0.0625 |
| 0.0575 | 1.0037 | 10000 | 0.0626 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for ymoslem/xlm-roberta-base-qe-lr5e-05-v1
Base model
FacebookAI/xlm-roberta-base