|
--- |
|
base_model: demdecuong/vihealthbert-base-word |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- tmnam20/pretrained-vn-med-nli |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vihealthbert-w_unsup-SynPD |
|
results: |
|
- task: |
|
name: Masked Language Modeling |
|
type: fill-mask |
|
dataset: |
|
name: tmnam20/pretrained-vn-med-nli all |
|
type: tmnam20/pretrained-vn-med-nli |
|
args: all |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.686153705209395 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# vihealthbert-w_unsup-SynPD |
|
|
|
This model is a fine-tuned version of [demdecuong/vihealthbert-base-word](https://huggingface.co/demdecuong/vihealthbert-base-word) on the tmnam20/pretrained-vn-med-nli all dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5768 |
|
- Accuracy: 0.6862 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 16 |
|
- seed: 21363 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:-----:|:---------------:|:--------:| |
|
| 7.0234 | 0.8616 | 5000 | 2.5909 | 0.5576 | |
|
| 5.2736 | 1.7232 | 10000 | 2.1890 | 0.5962 | |
|
| 4.9126 | 2.5849 | 15000 | 1.9095 | 0.6381 | |
|
| 4.791 | 3.4465 | 20000 | 1.8286 | 0.6469 | |
|
| 4.6538 | 4.3081 | 25000 | 1.7144 | 0.6644 | |
|
| 4.5846 | 5.1697 | 30000 | 1.6779 | 0.6704 | |
|
| 4.5568 | 6.0314 | 35000 | 1.6362 | 0.6766 | |
|
| 4.5079 | 6.8930 | 40000 | 1.6008 | 0.6814 | |
|
| 4.469 | 7.7546 | 45000 | 1.6064 | 0.6805 | |
|
| 4.4514 | 8.6162 | 50000 | 1.5800 | 0.6852 | |
|
| 4.4317 | 9.4779 | 55000 | 1.5540 | 0.6880 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
