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---
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
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