---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv2_new_pretrain_w_init_48_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: 0.25026626408652064
---

<!-- 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_pretrain_w_init_48_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2569
- Pearson: 0.2426
- Spearmanr: 0.2503
- Combined Score: 0.2465

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3064        | 1.0   | 45   | 2.2784          | 0.1492  | 0.1433    | 0.1462         |
| 1.9454        | 2.0   | 90   | 2.2773          | 0.2660  | 0.2546    | 0.2603         |
| 1.7733        | 3.0   | 135  | 2.2569          | 0.2426  | 0.2503    | 0.2465         |
| 1.4752        | 4.0   | 180  | 2.3395          | 0.2833  | 0.3025    | 0.2929         |
| 1.083         | 5.0   | 225  | 2.4140          | 0.3017  | 0.3066    | 0.3042         |
| 0.8694        | 6.0   | 270  | 2.8854          | 0.2790  | 0.3025    | 0.2908         |
| 0.7272        | 7.0   | 315  | 2.8901          | 0.3041  | 0.3066    | 0.3054         |
| 0.6008        | 8.0   | 360  | 2.6252          | 0.2837  | 0.2833    | 0.2835         |


### Framework versions

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