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distilbert-science-exam-sm
This model is a fine-tuned version of distilbert-base-cased on the LLM Science Exam dataset from Kaggle for MCQA. It achieves the following results on the evaluation set:
- Loss: 1.2390
- Accuracy: 0.7
Intended uses & limitations
Multiple Choice Question & Answer on Medical Topics
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.0428 | 0.5 |
| No log | 2.0 | 12 | 1.3253 | 0.5 |
| No log | 3.0 | 18 | 1.2390 | 0.7 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.0
- Tokenizers 0.13.3
