transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v1_complete_training_new_48 base_model:finetune:gokuls/bert_12_layer_model_v1_complete_training_new_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
datasets:
- glue
language:
- en
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_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: 0.385826216097769
      name: Spearmanr
---

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# hBERTv1_new_pretrain_48_ver2_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0507
- Pearson: 0.3913
- Spearmanr: 0.3858
- Combined Score: 0.3885

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.2439        | 1.0   | 90   | 2.2582          | 0.1118  | 0.1205    | 0.1162         |
| 1.9712        | 2.0   | 180  | 2.5514          | 0.2121  | 0.2109    | 0.2115         |
| 1.6254        | 3.0   | 270  | 2.6339          | 0.2885  | 0.2887    | 0.2886         |
| 1.2292        | 4.0   | 360  | 2.1543          | 0.3642  | 0.3666    | 0.3654         |
| 0.9444        | 5.0   | 450  | 2.6438          | 0.3529  | 0.3577    | 0.3553         |
| 0.7567        | 6.0   | 540  | 2.3755          | 0.3820  | 0.3872    | 0.3846         |
| 0.5838        | 7.0   | 630  | 2.0507          | 0.3913  | 0.3858    | 0.3885         |
| 0.5032        | 8.0   | 720  | 2.5227          | 0.4037  | 0.4071    | 0.4054         |
| 0.4112        | 9.0   | 810  | 2.1436          | 0.4072  | 0.3988    | 0.4030         |
| 0.3551        | 10.0  | 900  | 2.1501          | 0.4069  | 0.4004    | 0.4037         |
| 0.2961        | 11.0  | 990  | 2.2744          | 0.4137  | 0.4080    | 0.4109         |
| 0.256         | 12.0  | 1080 | 2.3612          | 0.4115  | 0.4038    | 0.4076         |


### Framework versions

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