---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_data_aug_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.318246541903987
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hBERTv2_data_aug_mnli

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0988
- Accuracy: 0.3182

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 1.0988        | 1.0   | 31440  | 1.0988          | 0.3182   |
| 1.0985        | 2.0   | 62880  | 1.0992          | 0.3182   |
| 1.0985        | 3.0   | 94320  | 1.0991          | 0.3182   |
| 1.0985        | 4.0   | 125760 | 1.0991          | 0.3182   |
| 1.0985        | 5.0   | 157200 | 1.0988          | 0.3182   |
| 1.0985        | 6.0   | 188640 | 1.0988          | 0.3182   |
| 1.0985        | 7.0   | 220080 | 1.0988          | 0.3182   |
| 1.0985        | 8.0   | 251520 | 1.0988          | 0.3182   |
| 1.0985        | 9.0   | 282960 | 1.0988          | 0.3182   |
| 1.0985        | 10.0  | 314400 | 1.0988          | 0.3182   |
| 1.0985        | 11.0  | 345840 | 1.0988          | 0.3182   |
| 1.0985        | 12.0  | 377280 | 1.0988          | 0.3182   |
| 1.0985        | 13.0  | 408720 | 1.0988          | 0.3182   |
| 1.0985        | 14.0  | 440160 | 1.0988          | 0.3182   |
| 1.0985        | 15.0  | 471600 | 1.0988          | 0.3182   |


### Framework versions

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