transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 base_model:finetune:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48
datasets:
- glue
language:
- en
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_w_init_48_ver2_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.19761262239980293
      name: Spearmanr
---

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# hBERTv2_new_pretrain_w_init_48_ver2_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: 2.2194
- Pearson: 0.2187
- Spearmanr: 0.1976
- Combined Score: 0.2081

## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3584        | 1.0   | 90   | 2.3085          | 0.1702  | 0.1471    | 0.1586         |
| 2.0513        | 2.0   | 180  | 2.4060          | 0.1479  | 0.1342    | 0.1411         |
| 1.9851        | 3.0   | 270  | 2.4888          | 0.0897  | 0.1163    | 0.1030         |
| 1.8287        | 4.0   | 360  | 2.7571          | 0.1643  | 0.1827    | 0.1735         |
| 1.6845        | 5.0   | 450  | 2.2194          | 0.2187  | 0.1976    | 0.2081         |
| 1.6892        | 6.0   | 540  | 2.4431          | 0.1882  | 0.1858    | 0.1870         |
| 1.5272        | 7.0   | 630  | 2.6124          | 0.1433  | 0.1572    | 0.1503         |
| 1.402         | 8.0   | 720  | 2.8100          | 0.1605  | 0.1671    | 0.1638         |
| 1.3122        | 9.0   | 810  | 2.7081          | 0.1298  | 0.1428    | 0.1363         |
| 1.187         | 10.0  | 900  | 2.8638          | 0.1724  | 0.1825    | 0.1775         |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
