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viettel-crossencoder-reader-improved-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: 1.3014
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 |
|---|---|---|---|
| 2.7591 | 0.32 | 500 | 1.7871 |
| 1.7222 | 0.65 | 1000 | 1.5235 |
| 1.5485 | 0.97 | 1500 | 1.3767 |
| 1.2533 | 1.29 | 2000 | 1.3574 |
| 1.194 | 1.62 | 2500 | 1.3367 |
| 1.1536 | 1.94 | 3000 | 1.3014 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
