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--- |
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license: mit |
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language: |
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- ja |
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tags: |
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- generated_from_trainer |
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- ja_qu_ad |
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- bert |
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datasets: SkelterLabsInc/JaQuAD |
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widget: |
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- text: どこへ出かけた？ |
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context: 2015年9月1日、私は横浜へ車で出かけました。映画を観た後に中華街まで電車で行き、昼ご飯は重慶飯店で中華フルコースを食べました。 |
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model-index: |
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- name: xlm-roberta-base-finetuned-JaQuAD |
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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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# xlm-roberta-base-finetuned-JaQuAD |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [JaQuAD](https://huggingface.co/datasets/SkelterLabsInc/JaQuAD) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7495 |
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## Model description |
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More information needed |
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## Intended uses |
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```python |
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import torch |
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from transformers import AutoModelForQuestionAnswering, AutoTokenizer |
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model_name = "thkkvui/xlm-roberta-base-finetuned-JaQuAD" |
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model = (AutoModelForQuestionAnswering.from_pretrained(model_name)) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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text = "2015年9月1日、私は横浜へ車で出かけました。映画を観た後に中華街まで電車で行き、昼ご飯は重慶飯店で中華フルコースを食べました。" |
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questions= ["どこへ出かけた？", "電車に乗る前は何をしていた？", "重慶飯店で何を食べた？", "いつ横浜に出かけた？"] |
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for question in questions: |
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inputs = tokenizer.encode_plus(question, text, add_special_tokens=True, return_tensors="pt") |
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with torch.no_grad(): |
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output = model(**inputs) |
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answer_start = torch.argmax(output.start_logits) |
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answer_end = torch.argmax(output.end_logits) |
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answer_tokens = inputs.input_ids[0, answer_start : answer_end + 1] |
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answer = tokenizer.decode(answer_tokens) |
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print(f"質問: {question} -> 回答: {answer}") |
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``` |
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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: 6e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8661 | 1.0 | 1985 | 0.8036 | |
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| 0.5348 | 2.0 | 3970 | 0.7495 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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