Multiple-choice-qa
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5306
- Accuracy: 0.7961
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: 5e-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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7347 | 1.0 | 2299 | 0.5306 | 0.7961 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the HF Inference API does not support transformers models with pipeline type multiple-choice
Model tree for Hemg/Multiple-choice-qa
Base model
google-bert/bert-base-uncased