---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_data_aug_sst2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE SST2
      type: glue
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7855504587155964
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hBERTv1_data_aug_sst2

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 SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6087
- Accuracy: 0.7856

## 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 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2892        | 1.0   | 4374  | 0.6087          | 0.7856   |
| 0.1628        | 2.0   | 8748  | 0.7398          | 0.7810   |
| 0.1151        | 3.0   | 13122 | 0.8492          | 0.8016   |
| 0.0917        | 4.0   | 17496 | 1.0381          | 0.7867   |
| 0.0862        | 5.0   | 21870 | 0.9657          | 0.7867   |
| 0.0762        | 6.0   | 26244 | 1.0815          | 0.7821   |


### Framework versions

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