license: mit | |
tags: | |
- generated_from_trainer | |
datasets: | |
- ja_qu_ad | |
model-index: | |
- name: xlm-roberta-base-finetuned-JaQuAD | |
results: [] | |
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# xlm-roberta-base-finetuned-JaQuAD | |
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the ja_qu_ad dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.7495 | |
## 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: 6e-05 | |
- train_batch_size: 16 | |
- eval_batch_size: 16 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- lr_scheduler_warmup_steps: 50 | |
- num_epochs: 2 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | | |
|:-------------:|:-----:|:----:|:---------------:| | |
| 0.8661 | 1.0 | 1985 | 0.8036 | | |
| 0.5348 | 2.0 | 3970 | 0.7495 | | |
### Framework versions | |
- Transformers 4.30.2 | |
- Pytorch 2.0.1 | |
- Datasets 2.13.1 | |
- Tokenizers 0.13.3 | |