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: hBERTv1_data_aug_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.4294216093279403
      name: Spearmanr
---

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# hBERTv1_data_aug_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1](https://huggingface.co/gokuls/bert_12_layer_model_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1580
- Pearson: 0.4471
- Spearmanr: 0.4294
- Combined Score: 0.4383

## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 0.5955        | 1.0   | 1259 | 2.1996          | 0.4857  | 0.4640    | 0.4748         |
| 0.1017        | 2.0   | 2518 | 2.1580          | 0.4471  | 0.4294    | 0.4383         |
| 0.06          | 3.0   | 3777 | 2.5480          | 0.4052  | 0.3733    | 0.3892         |
| 0.0454        | 4.0   | 5036 | 2.1594          | 0.4500  | 0.4193    | 0.4347         |
| 0.038         | 5.0   | 6295 | 2.6866          | 0.4071  | 0.3658    | 0.3865         |
| 0.0318        | 6.0   | 7554 | 2.8519          | 0.3891  | 0.3435    | 0.3663         |
| 0.0283        | 7.0   | 8813 | 2.6783          | 0.3836  | 0.3464    | 0.3650         |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
