|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- null |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa-1 |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa-1 |
|
|
|
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6660 |
|
- Accuracy: 0.7 |
|
|
|
## 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: 1e-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 | 0.8471 | 0.58 | |
|
| No log | 2.0 | 114 | 0.8450 | 0.58 | |
|
| No log | 3.0 | 171 | 0.7846 | 0.58 | |
|
| No log | 4.0 | 228 | 0.8649 | 0.58 | |
|
| No log | 5.0 | 285 | 0.7220 | 0.68 | |
|
| No log | 6.0 | 342 | 0.7395 | 0.66 | |
|
| No log | 7.0 | 399 | 0.7198 | 0.72 | |
|
| No log | 8.0 | 456 | 0.6417 | 0.72 | |
|
| 0.7082 | 9.0 | 513 | 0.6265 | 0.74 | |
|
| 0.7082 | 10.0 | 570 | 0.6660 | 0.7 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.10.2 |
|
- Pytorch 1.9.0+cu102 |
|
- Datasets 1.12.0 |
|
- Tokenizers 0.10.3 |
|
|
