transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: add_BERT_24_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: 0.6105765151286849
      name: Spearmanr
---

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# add_BERT_24_stsb

This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4492
- Pearson: 0.6090
- Spearmanr: 0.6106
- Combined Score: 0.6098

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.1466        | 1.0   | 45   | 2.2698          | 0.3930  | 0.3260    | 0.3595         |
| 1.4589        | 2.0   | 90   | 1.7726          | 0.5150  | 0.5141    | 0.5145         |
| 1.0006        | 3.0   | 135  | 1.4492          | 0.6090  | 0.6106    | 0.6098         |
| 0.6766        | 4.0   | 180  | 1.8200          | 0.5635  | 0.5672    | 0.5654         |
| 0.4849        | 5.0   | 225  | 2.1591          | 0.5213  | 0.5212    | 0.5213         |
| 0.3823        | 6.0   | 270  | 1.8541          | 0.5717  | 0.5716    | 0.5717         |
| 0.3158        | 7.0   | 315  | 1.8647          | 0.5777  | 0.5741    | 0.5759         |
| 0.2816        | 8.0   | 360  | 1.4985          | 0.6097  | 0.6083    | 0.6090         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
