transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v2_complete_training_new_48 base_model:finetune:gokuls/bert_12_layer_model_v2_complete_training_new_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v2_complete_training_new_48
datasets:
- glue
language:
- en
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_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: 0.38294286179733106
      name: Spearmanr
---

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# hBERTv2_new_pretrain_48_ver2_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0659
- Pearson: 0.3927
- Spearmanr: 0.3829
- Combined Score: 0.3878

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3158        | 1.0   | 90   | 2.7785          | 0.1355  | 0.1181    | 0.1268         |
| 2.0193        | 2.0   | 180  | 2.6566          | 0.1954  | 0.2050    | 0.2002         |
| 1.7471        | 3.0   | 270  | 2.5202          | 0.2578  | 0.2647    | 0.2612         |
| 1.5032        | 4.0   | 360  | 3.0601          | 0.2605  | 0.2732    | 0.2668         |
| 1.1825        | 5.0   | 450  | 2.3378          | 0.3150  | 0.3180    | 0.3165         |
| 0.8788        | 6.0   | 540  | 2.3657          | 0.3437  | 0.3421    | 0.3429         |
| 0.6987        | 7.0   | 630  | 2.0659          | 0.3927  | 0.3829    | 0.3878         |
| 0.5879        | 8.0   | 720  | 2.6712          | 0.3631  | 0.3636    | 0.3634         |
| 0.4865        | 9.0   | 810  | 2.3066          | 0.3665  | 0.3625    | 0.3645         |
| 0.4233        | 10.0  | 900  | 2.2781          | 0.3753  | 0.3695    | 0.3724         |
| 0.3628        | 11.0  | 990  | 2.4672          | 0.3848  | 0.3758    | 0.3803         |
| 0.3113        | 12.0  | 1080 | 2.4339          | 0.3873  | 0.3809    | 0.3841         |


### Framework versions

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