|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- ncbi_disease |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: finetuned-biogpt |
|
results: |
|
- task: |
|
name: Token Classification |
|
type: token-classification |
|
dataset: |
|
name: ncbi_disease |
|
type: ncbi_disease |
|
config: ncbi_disease |
|
split: test |
|
args: ncbi_disease |
|
metrics: |
|
- name: Precision |
|
type: precision |
|
value: 0.0761904761904762 |
|
- name: Recall |
|
type: recall |
|
value: 0.058333333333333334 |
|
- name: F1 |
|
type: f1 |
|
value: 0.06607669616519174 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9220180016640194 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# finetuned-biogpt |
|
|
|
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2503 |
|
- Precision: 0.0762 |
|
- Recall: 0.0583 |
|
- F1: 0.0661 |
|
- Accuracy: 0.9220 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 2 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 340 | 0.2644 | 0.0426 | 0.0281 | 0.0339 | 0.9183 | |
|
| 0.3055 | 2.0 | 680 | 0.2503 | 0.0762 | 0.0583 | 0.0661 | 0.9220 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.1 |
|
- Pytorch 2.0.0+cu118 |
|
- Datasets 2.11.0 |
|
- Tokenizers 0.13.3 |
|
|