---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv2_new_pretrain_48_emb_com_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: 0.30729552140330846
---

<!-- 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_48_emb_com_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0889
- Pearson: 0.3123
- Spearmanr: 0.3073
- Combined Score: 0.3098

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.398         | 1.0   | 45   | 3.0621          | 0.0972  | 0.1007    | 0.0990         |
| 2.0392        | 2.0   | 90   | 2.3674          | 0.1058  | 0.1011    | 0.1034         |
| 1.967         | 3.0   | 135  | 2.2296          | 0.1449  | 0.1432    | 0.1441         |
| 1.8176        | 4.0   | 180  | 2.6036          | 0.2055  | 0.2169    | 0.2112         |
| 1.6744        | 5.0   | 225  | 2.2119          | 0.2516  | 0.2534    | 0.2525         |
| 1.4727        | 6.0   | 270  | 2.0889          | 0.3123  | 0.3073    | 0.3098         |
| 1.1852        | 7.0   | 315  | 2.6372          | 0.3609  | 0.3543    | 0.3576         |
| 0.9895        | 8.0   | 360  | 2.5881          | 0.3312  | 0.3322    | 0.3317         |
| 0.8254        | 9.0   | 405  | 2.1746          | 0.3991  | 0.3974    | 0.3983         |
| 0.6759        | 10.0  | 450  | 2.7671          | 0.3693  | 0.3663    | 0.3678         |
| 0.558         | 11.0  | 495  | 2.5954          | 0.3967  | 0.3942    | 0.3955         |


### Framework versions

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