---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv1_new_pretrain_w_init__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: 0.08916919703003628
---

<!-- 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_w_init__stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2584
- Pearson: 0.0949
- Spearmanr: 0.0892
- Combined Score: 0.0920

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.5056        | 1.0   | 45   | 2.2584          | 0.0949  | 0.0892    | 0.0920         |
| 2.1254        | 2.0   | 90   | 2.6871          | 0.1250  | 0.1231    | 0.1241         |
| 1.9839        | 3.0   | 135  | 2.2709          | 0.1790  | 0.1840    | 0.1815         |
| 1.6299        | 4.0   | 180  | 2.5115          | 0.2691  | 0.2797    | 0.2744         |
| 1.3155        | 5.0   | 225  | 2.4555          | 0.3453  | 0.3437    | 0.3445         |
| 0.9686        | 6.0   | 270  | 2.8004          | 0.4571  | 0.4406    | 0.4489         |


### Framework versions

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