---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_qnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QNLI
      type: glue
      config: qnli
      split: validation
      args: qnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5053999633900788
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hBERTv2_qnli

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 QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6930
- Accuracy: 0.5054

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6968        | 1.0   | 410  | 0.6952          | 0.5054   |
| 0.6943        | 2.0   | 820  | 0.6932          | 0.4946   |
| 0.6937        | 3.0   | 1230 | 0.6933          | 0.5054   |
| 0.6934        | 4.0   | 1640 | 0.6931          | 0.5054   |
| 0.6934        | 5.0   | 2050 | 0.6931          | 0.5054   |
| 0.6933        | 6.0   | 2460 | 0.6930          | 0.5054   |
| 0.6933        | 7.0   | 2870 | 0.6931          | 0.5054   |
| 0.6932        | 8.0   | 3280 | 0.6930          | 0.5054   |
| 0.6932        | 9.0   | 3690 | 0.6934          | 0.4946   |
| 0.6932        | 10.0  | 4100 | 0.6930          | 0.5054   |
| 0.6932        | 11.0  | 4510 | 0.6931          | 0.4946   |
| 0.6933        | 12.0  | 4920 | 0.6934          | 0.4946   |
| 0.6932        | 13.0  | 5330 | 0.6931          | 0.4946   |


### Framework versions

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