metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: pritamdeka/PubMedBERT-MNLI-MEDNLI
results: []
pritamdeka/PubMedBERT-MNLI-MEDNLI
This model is a fine-tuned version of PubMedBERT on the MNLI dataset first and then on the MedNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.9501
- Accuracy: 0.8667
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: 20.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5673 | 1.42 | 500 | 0.4358 | 0.8437 |
| 0.2898 | 2.85 | 1000 | 0.4845 | 0.8523 |
| 0.1669 | 4.27 | 1500 | 0.6233 | 0.8573 |
| 0.1087 | 5.7 | 2000 | 0.7263 | 0.8573 |
| 0.0728 | 7.12 | 2500 | 0.8841 | 0.8638 |
| 0.0512 | 8.55 | 3000 | 0.9501 | 0.8667 |
| 0.0372 | 9.97 | 3500 | 1.0440 | 0.8566 |
| 0.0262 | 11.4 | 4000 | 1.0770 | 0.8609 |
| 0.0243 | 12.82 | 4500 | 1.0931 | 0.8616 |
| 0.023 | 14.25 | 5000 | 1.1088 | 0.8631 |
| 0.0163 | 15.67 | 5500 | 1.1264 | 0.8581 |
| 0.0111 | 17.09 | 6000 | 1.1541 | 0.8616 |
| 0.0098 | 18.52 | 6500 | 1.1542 | 0.8631 |
| 0.0074 | 19.94 | 7000 | 1.1653 | 0.8638 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1