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bert-base-historic-multilingual-64k-td-cased-squad-en
Nadav/bert-base-historic-multilingual-64k-td-cased-squad-en
bert-base-historic-multilingual-64k-td-cased-squad-en is a question answering model from Nadav. 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
- Dec 5, 2022
- Updated
- Dec 6, 2022
- SHA
- a712e0f4
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-base-historic-multilingual-64k-td-cased-squad-en
This model is a fine-tuned version of dbmdz/bert-base-historic-multilingual-64k-td-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5474
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9315 | 1.0 | 4659 | 1.7399 |
| 1.5775 | 2.0 | 9318 | 1.5474 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Dec 5, 2022
- Updated
- Dec 6, 2022