metadata
tags:
- generated_from_trainer
datasets:
- null
metrics:
- accuracy
model_index:
- name: biobert-v1.1-finetuned-pubmedqa-adapter
results:
- task:
name: Text Classification
type: text-classification
metric:
name: Accuracy
type: accuracy
value: 0.48
biobert-v1.1-finetuned-pubmedqa-adapter
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0910
- Accuracy: 0.48
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: 0.003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 57 | 0.9848 | 0.58 |
| No log | 2.0 | 114 | 0.8537 | 0.58 |
| No log | 3.0 | 171 | 0.9565 | 0.42 |
| No log | 4.0 | 228 | 0.9659 | 0.56 |
| No log | 5.0 | 285 | 0.9763 | 0.6 |
| No log | 6.0 | 342 | 1.0647 | 0.66 |
| No log | 7.0 | 399 | 1.4305 | 0.6 |
| No log | 8.0 | 456 | 2.0545 | 0.56 |
| 0.6957 | 9.0 | 513 | 2.2438 | 0.5 |
| 0.6957 | 10.0 | 570 | 2.0910 | 0.48 |
Framework versions
- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3