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xlm-r-qa-squad1.1-squad2.0-tf-3
mrizalf7/xlm-r-qa-squad1.1-squad2.0-tf-3
xlm-r-qa-squad1.1-squad2.0-tf-3 is a question answering model from mrizalf7. 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
- xlm-roberta
- Access
- Public
- Created
- Jul 15, 2023
- Updated
- Jul 15, 2023
- SHA
- 27d48cb7
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. -->
xlm-r-qa-squad1.1-squad2.0-tf-3
This model is a fine-tuned version of mrizalf7/xlm-r-qa-squad-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2377
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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9462 | 1.0 | 5437 | 2.0332 |
| 0.6874 | 2.0 | 10874 | 2.2377 |
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
- xlm-roberta
- License
- mit
- Created
- Jul 15, 2023
- Updated
- Jul 15, 2023