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vi-adapter-32
subhasisj/vi-adapter-32
vi-adapter-32 is a question answering model from subhasisj. 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
- xlm-roberta
- Access
- Public
- Created
- May 21, 2022
- Updated
- May 21, 2022
- SHA
- 0662d668
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. -->
vi-adapter-32
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.4211
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 356 | 5.6984 |
| 5.7565 | 2.0 | 712 | 5.5596 |
| 5.5609 | 3.0 | 1068 | 5.4781 |
| 5.5609 | 4.0 | 1424 | 5.4349 |
| 5.4654 | 5.0 | 1780 | 5.4211 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- Created
- May 21, 2022
- Updated
- May 21, 2022