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distilbert-base-uncased-finetuned-squac
adrinanou/distilbert-base-uncased-finetuned-squac
distilbert-base-uncased-finetuned-squac is a question answering model from adrinanou. 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
- Aug 21, 2023
- Updated
- Aug 24, 2023
- SHA
- efb6020c
Try a prompt
Base models
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-squac
This model is a fine-tuned version of distilbert-base-uncased on an Extractive QuestionAnswering dataset(SQuAC). It achieves the following results on the evaluation set:
- Loss: 2.0973
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|
| 3.0135 | 1.0 | 842 | 2.2648 |
| 2.1735 | 2.0 | 1684 | 2.1575 |
| 1.9441 | 3.0 | 2526 | 2.0973 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Question Answering
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 21, 2023
- Updated
- Aug 24, 2023