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sber-full-test
ruselkomp/sber-full-test
sber-full-test is a question answering model from ruselkomp. 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
- May 14, 2022
- Updated
- May 14, 2022
- SHA
- e051a3da
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. -->
sber-full-test
This model is a fine-tuned version of sberbank-ai/sbert_large_nlu_ru on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4148
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: 5
- eval_batch_size: 5
- 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 |
|---|---|---|---|
| 1.0779 | 1.0 | 9046 | 1.3850 |
| 0.7429 | 2.0 | 18092 | 1.1795 |
| 0.446 | 3.0 | 27138 | 1.4148 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.2.2.dev0
- Tokenizers 0.12.1
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- Created
- May 14, 2022
- Updated
- May 14, 2022