---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv1_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: 0.21371019463671115
---

<!-- 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_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: 2.1733
- Pearson: 0.2374
- Spearmanr: 0.2137
- Combined Score: 0.2256

## 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: 96
- eval_batch_size: 96
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3601        | 1.0   | 60   | 2.6639          | 0.1059  | 0.1080    | 0.1069         |
| 1.9983        | 2.0   | 120  | 2.1733          | 0.2374  | 0.2137    | 0.2256         |
| 1.7079        | 3.0   | 180  | 2.5000          | 0.1872  | 0.1967    | 0.1920         |
| 1.3775        | 4.0   | 240  | 3.1203          | 0.2177  | 0.2251    | 0.2214         |
| 1.1218        | 5.0   | 300  | 2.8260          | 0.2609  | 0.2598    | 0.2603         |
| 0.8882        | 6.0   | 360  | 2.5413          | 0.3099  | 0.3062    | 0.3081         |
| 0.728         | 7.0   | 420  | 2.4024          | 0.3429  | 0.3468    | 0.3448         |


### Framework versions

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