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fewshot-qa-002-20230613-003
intanm/fewshot-qa-002-20230613-003
fewshot-qa-002-20230613-003 is a question answering model from intanm. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- cc-by-4.0
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jun 13, 2023
- Updated
- Jun 13, 2023
- SHA
- df6723f4
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. -->
fewshot-qa-002-20230613-003
This model is a fine-tuned version of deepset/xlm-roberta-base-squad2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.3842
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 208 | 2.5896 |
| No log | 2.0 | 416 | 2.6143 |
| 2.487 | 3.0 | 624 | 2.7156 |
| 2.487 | 4.0 | 832 | 3.1187 |
| 1.2936 | 5.0 | 1040 | 3.3531 |
| 1.2936 | 6.0 | 1248 | 3.7272 |
| 1.2936 | 7.0 | 1456 | 3.9238 |
| 0.6852 | 8.0 | 1664 | 4.3116 |
| 0.6852 | 9.0 | 1872 | 4.3842 |
| 0.3944 | 10.0 | 2080 | 4.3842 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- License
- cc-by-4.0
- Created
- Jun 13, 2023
- Updated
- Jun 13, 2023