---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv1_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: 0.7471924680940966
---

<!-- 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_48_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9800
- Pearson: 0.7515
- Spearmanr: 0.7472
- Combined Score: 0.7493

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.5456        | 1.0   | 45   | 2.2706          | 0.1246  | 0.1141    | 0.1194         |
| 2.0514        | 2.0   | 90   | 2.0613          | 0.5266  | 0.5198    | 0.5232         |
| 1.3837        | 3.0   | 135  | 1.1984          | 0.6853  | 0.6942    | 0.6897         |
| 1.0297        | 4.0   | 180  | 1.6176          | 0.6869  | 0.6961    | 0.6915         |
| 0.8064        | 5.0   | 225  | 1.1444          | 0.7476  | 0.7445    | 0.7460         |
| 0.604         | 6.0   | 270  | 1.2754          | 0.7422  | 0.7450    | 0.7436         |
| 0.4818        | 7.0   | 315  | 1.1407          | 0.7687  | 0.7673    | 0.7680         |
| 0.3905        | 8.0   | 360  | 1.1860          | 0.7560  | 0.7604    | 0.7582         |
| 0.3476        | 9.0   | 405  | 0.9800          | 0.7515  | 0.7472    | 0.7493         |
| 0.2819        | 10.0  | 450  | 1.0156          | 0.7521  | 0.7507    | 0.7514         |
| 0.2418        | 11.0  | 495  | 1.0174          | 0.7516  | 0.7480    | 0.7498         |
| 0.2068        | 12.0  | 540  | 1.2367          | 0.7530  | 0.7523    | 0.7527         |
| 0.1863        | 13.0  | 585  | 1.0073          | 0.7491  | 0.7468    | 0.7480         |
| 0.1929        | 14.0  | 630  | 1.0470          | 0.7517  | 0.7505    | 0.7511         |


### Framework versions

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