Downloads · 30 days
48
2% of all-time downloads
roberta-base-bne-finetuned-sqac
nlp-en-es/roberta-base-bne-finetuned-sqac
roberta-base-bne-finetuned-sqac is a question answering model from nlp-en-es. 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. --
All-time downloads
2.1K
Public
Parameters
124M
1.5 GB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.bin496 MB · 50%
Parameter types
How the weights are stored.
F32124M · 100%
Try a prompt
Base models
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. -->
roberta-base-bne-finetuned-sqac
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the sqac dataset. It achieves the following results on the evaluation set:
- Loss: 1.2111
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 |
|---|---|---|---|
| 0.9971 | 1.0 | 1196 | 0.8646 |
| 0.482 | 2.0 | 2392 | 0.9334 |
| 0.1652 | 3.0 | 3588 | 1.2111 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
- Task
- Question Answering
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Languages
- es
- Created
- Mar 2, 2022
- Updated
- Dec 20, 2023