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distilbert-base-uncased-finetuned-advers
T-qualizer/distilbert-base-uncased-finetuned-advers
distilbert-base-uncased-finetuned-advers is a question answering model from T-qualizer. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Mar 13, 2022
- Updated
- Mar 14, 2022
- SHA
- 27a1d890
Try a prompt
Datasets
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. -->
distilbert-base-uncased-finetuned-advers
This model is a fine-tuned version of distilbert-base-uncased on the adversarial_qa dataset. It achieves the following results on the evaluation set:
- Loss: 3.6462
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: 9e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.6424 | 0.18 | 3000 | 3.6462 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
- Task
- Question Answering
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 13, 2022
- Updated
- Mar 14, 2022