---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv2_new_no_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: 0.20926356415783265
---

<!-- 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. -->

# hBERTv2_new_no_pretrain_stsb

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2174
- Pearson: 0.1946
- Spearmanr: 0.2093
- Combined Score: 0.2019

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3893        | 1.0   | 45   | 2.3698          | 0.1204  | 0.1138    | 0.1171         |
| 1.9589        | 2.0   | 90   | 2.2174          | 0.1946  | 0.2093    | 0.2019         |
| 1.6743        | 3.0   | 135  | 2.3481          | 0.2144  | 0.2207    | 0.2175         |
| 1.4068        | 4.0   | 180  | 2.5921          | 0.2472  | 0.2519    | 0.2496         |
| 1.2205        | 5.0   | 225  | 2.6279          | 0.2718  | 0.2701    | 0.2709         |
| 0.9353        | 6.0   | 270  | 2.5440          | 0.3117  | 0.3213    | 0.3165         |
| 0.7662        | 7.0   | 315  | 2.3053          | 0.3501  | 0.3519    | 0.3510         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3