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roberta-base-uy22-cased-finetuned-nlquad
jmachado/roberta-base-uy22-cased-finetuned-nlquad
roberta-base-uy22-cased-finetuned-nlquad is a question answering model from jmachado. 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
- roberta
- Access
- Public
- Created
- Nov 16, 2023
- Updated
- Nov 29, 2023
- SHA
- 76deed17
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. -->
roberta-base-uy22-cased-finetuned-nlquad
This model is a fine-tuned version of pln-udelar/roberta-base-uy22-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.8520
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: 1
- eval_batch_size: 1
- 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 |
|---|---|---|---|
| 4.9142 | 1.0 | 288408 | 4.8520 |
| 4.9093 | 2.0 | 576816 | 4.8520 |
| 4.9146 | 3.0 | 865224 | 4.8520 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.13.2
- Tokenizers 0.12.1
- Task
- Question Answering
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Nov 16, 2023
- Updated
- Nov 29, 2023