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indobert-finetune-tydiqa-transfer-indoqa
andreaschandra/indobert-finetune-tydiqa-transfer-indoqa
indobert-finetune-tydiqa-transfer-indoqa is a question answering model from andreaschandra. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Oct 21, 2022
- Updated
- Oct 31, 2022
- SHA
- 25a51b8e
Try a prompt
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
indobert-finetune-tydiqa-transfer-indoqa
This model is a fine-tuned version of indolem/indobert-base-uncased on the tydiqa dataset. It achieves the following results on the evaluation set:
- Loss: 2.3210
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: 1e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.162 | 1.0 | 241 | 3.2961 |
| 1.9671 | 2.0 | 482 | 2.4509 |
| 1.457 | 3.0 | 723 | 2.3005 |
| 1.2349 | 4.0 | 964 | 2.2628 |
| 1.0681 | 5.0 | 1205 | 2.1436 |
| 0.9338 | 6.0 | 1446 | 2.1978 |
| 0.8523 | 7.0 | 1687 | 2.2780 |
| 0.7909 | 8.0 | 1928 | 2.2481 |
| 0.725 | 9.0 | 2169 | 2.2912 |
| 0.6977 | 10.0 | 2410 | 2.3210 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Oct 21, 2022
- Updated
- Oct 31, 2022