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viettel-crossencoder-reader-xlm-roberta-base-viquad
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2272
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: 2e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7448 | 0.33 | 500 | 1.7456 |
| 1.7323 | 0.66 | 1000 | 1.3974 |
| 1.5019 | 0.98 | 1500 | 1.2971 |
| 1.2067 | 1.31 | 2000 | 1.2769 |
| 1.1449 | 1.64 | 2500 | 1.2420 |
| 1.1442 | 1.97 | 3000 | 1.2272 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
