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Bert-CNNLSTM-QA-Pt-FULL
tyavika/Bert-CNNLSTM-QA-Pt-FULL
Bert-CNNLSTM-QA-Pt-FULL is a question answering model from tyavika. 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
- Jun 28, 2023
- Updated
- Jun 28, 2023
- SHA
- 6d0f7fb0
Try a prompt
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. -->
Bert-CNNLSTM-QA-Pt-FULL
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2581
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: 3e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2765 | 1.0 | 3290 | 1.1320 |
| 0.8879 | 2.0 | 6580 | 1.0397 |
| 0.5987 | 3.0 | 9870 | 1.1484 |
| 0.3994 | 4.0 | 13160 | 1.2581 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 28, 2023
- Updated
- Jun 28, 2023