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mbert-quoref-webis-2
intanm/mbert-quoref-webis-2
mbert-quoref-webis-2 is a question answering model from intanm. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Oct 19, 2023
- Updated
- Oct 21, 2023
- SHA
- 567a6f97
Try a prompt
Base models
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. -->
mbert-idkmrc-webis-2
This model is a fine-tuned version of intanm/mbert-quoref on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.1719
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 200 | 3.0455 |
| No log | 2.0 | 400 | 2.9841 |
| 2.8889 | 3.0 | 600 | 3.1719 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Oct 19, 2023
- Updated
- Oct 21, 2023