---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv1_new_pretrain_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: 0.24765283238401
---

<!-- 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_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2275
- Pearson: 0.2386
- Spearmanr: 0.2477
- Combined Score: 0.2431

## 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: 128
- eval_batch_size: 128
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.2918        | 1.0   | 45   | 2.6098          | 0.1233  | 0.1129    | 0.1181         |
| 1.9907        | 2.0   | 90   | 2.4074          | 0.2000  | 0.1874    | 0.1937         |
| 1.6996        | 3.0   | 135  | 2.2275          | 0.2386  | 0.2477    | 0.2431         |
| 1.4403        | 4.0   | 180  | 2.5775          | 0.3060  | 0.3062    | 0.3061         |
| 1.1707        | 5.0   | 225  | 2.3220          | 0.3500  | 0.3356    | 0.3428         |
| 0.8313        | 6.0   | 270  | 2.4218          | 0.3881  | 0.3929    | 0.3905         |
| 0.6374        | 7.0   | 315  | 2.2601          | 0.3980  | 0.3955    | 0.3967         |
| 0.5371        | 8.0   | 360  | 2.6668          | 0.3626  | 0.3601    | 0.3614         |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3