|
--- |
|
language: |
|
- en |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- spearmanr |
|
model-index: |
|
- name: hBERTv1_stsb |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE STSB |
|
type: glue |
|
config: stsb |
|
split: validation |
|
args: stsb |
|
metrics: |
|
- name: Spearmanr |
|
type: spearmanr |
|
value: 0.7155715863961268 |
|
--- |
|
|
|
<!-- 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_stsb |
|
|
|
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1](https://huggingface.co/gokuls/bert_12_layer_model_v1) on the GLUE STSB dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1154 |
|
- Pearson: 0.7159 |
|
- Spearmanr: 0.7156 |
|
- Combined Score: 0.7157 |
|
|
|
## 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: 256 |
|
- eval_batch_size: 256 |
|
- seed: 10 |
|
- distributed_type: multi-GPU |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
|
| 4.0796 | 1.0 | 23 | 2.3017 | 0.0761 | 0.0547 | 0.0654 | |
|
| 2.0746 | 2.0 | 46 | 2.6181 | 0.0850 | 0.0772 | 0.0811 | |
|
| 1.9142 | 3.0 | 69 | 2.2963 | 0.1878 | 0.1852 | 0.1865 | |
|
| 1.6883 | 4.0 | 92 | 2.1866 | 0.4740 | 0.4777 | 0.4759 | |
|
| 1.1166 | 5.0 | 115 | 1.9367 | 0.6319 | 0.6450 | 0.6384 | |
|
| 0.7598 | 6.0 | 138 | 1.4188 | 0.6801 | 0.6888 | 0.6845 | |
|
| 0.5453 | 7.0 | 161 | 1.2720 | 0.6988 | 0.7001 | 0.6994 | |
|
| 0.3705 | 8.0 | 184 | 1.1154 | 0.7159 | 0.7156 | 0.7157 | |
|
| 0.2976 | 9.0 | 207 | 1.6889 | 0.6754 | 0.6807 | 0.6780 | |
|
| 0.2272 | 10.0 | 230 | 1.3627 | 0.6929 | 0.6899 | 0.6914 | |
|
| 0.1966 | 11.0 | 253 | 1.1278 | 0.7195 | 0.7167 | 0.7181 | |
|
| 0.1708 | 12.0 | 276 | 1.3476 | 0.7171 | 0.7165 | 0.7168 | |
|
| 0.1529 | 13.0 | 299 | 1.2614 | 0.6982 | 0.6942 | 0.6962 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.2 |
|
|
