|
--- |
|
language: |
|
- en |
|
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: hBERTv1_new_pretrain_w_init_48_ver2_qqp |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE QQP |
|
type: glue |
|
config: qqp |
|
split: validation |
|
args: qqp |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7601038832550087 |
|
- name: F1 |
|
type: f1 |
|
value: 0.6952012821721505 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# hBERTv1_new_pretrain_w_init_48_ver2_qqp |
|
|
|
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE QQP dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4918 |
|
- Accuracy: 0.7601 |
|
- F1: 0.6952 |
|
- Combined Score: 0.7277 |
|
|
|
## 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: 4e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 64 |
|
- seed: 10 |
|
- distributed_type: multi-GPU |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:| |
|
| 0.5279 | 1.0 | 5686 | 0.4918 | 0.7601 | 0.6952 | 0.7277 | |
|
| 0.4826 | 2.0 | 11372 | 0.5367 | 0.7644 | 0.6556 | 0.7100 | |
|
| 0.4943 | 3.0 | 17058 | 0.5223 | 0.7594 | 0.6440 | 0.7017 | |
|
| 0.492 | 4.0 | 22744 | 0.5379 | 0.7600 | 0.6465 | 0.7032 | |
|
| 0.505 | 5.0 | 28430 | 0.5431 | 0.7423 | 0.6507 | 0.6965 | |
|
| 0.5428 | 6.0 | 34116 | 0.5789 | 0.7089 | 0.6289 | 0.6689 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
