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bert-base-spanish-wwm-cased-finetuned-sqac
MMG/bert-base-spanish-wwm-cased-finetuned-sqac
bert-base-spanish-wwm-cased-finetuned-sqac is a question answering model from MMG. Use it when the input is a question plus a passage. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 1, 2021
- SHA
- 15da909d
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. -->
bert-base-spanish-wwm-cased-finetuned-sqac
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the sqac dataset. It achieves the following results on the evaluation set: {'exact_match': 62.017167, 'f1': 79.452767}
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 |
|---|---|---|---|
| 1.1335 | 1.0 | 1230 | 0.9346 |
| 0.6794 | 2.0 | 2460 | 0.8634 |
| 0.3992 | 3.0 | 3690 | 0.9662 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- Languages
- es
- Created
- Mar 2, 2022
- Updated
- Dec 1, 2021