metadata
tags:
- generated_from_trainer
datasets:
- null
metrics:
- accuracy
model-index:
- name: biobert-base-cased-v1.1-finetuned-pubmedqa
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.58
biobert-base-cased-v1.1-finetuned-pubmedqa
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2530
- Accuracy: 0.58
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: 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 | 0.9477 | 0.54 |
| No log | 2.0 | 114 | 0.9100 | 0.6 |
| No log | 3.0 | 171 | 0.9887 | 0.6 |
| No log | 4.0 | 228 | 1.5443 | 0.62 |
| No log | 5.0 | 285 | 1.5868 | 0.6 |
| No log | 6.0 | 342 | 1.9679 | 0.58 |
| No log | 7.0 | 399 | 2.1031 | 0.58 |
| No log | 8.0 | 456 | 2.1613 | 0.6 |
| 0.3344 | 9.0 | 513 | 2.2219 | 0.58 |
| 0.3344 | 10.0 | 570 | 2.2530 | 0.58 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3