---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv2_new_no_pretrain_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: 0.6351821343584111
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hBERTv2_new_no_pretrain_qnli

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6386
- Accuracy: 0.6352

## 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6866        | 1.0   | 819  | 0.6770          | 0.5570   |
| 0.652         | 2.0   | 1638 | 0.6468          | 0.6264   |
| 0.5986        | 3.0   | 2457 | 0.6386          | 0.6352   |
| 0.5144        | 4.0   | 3276 | 0.6930          | 0.6590   |
| 0.4272        | 5.0   | 4095 | 0.7034          | 0.6548   |
| 0.3558        | 6.0   | 4914 | 0.8171          | 0.6637   |
| 0.2874        | 7.0   | 5733 | 0.9057          | 0.6601   |
| 0.2391        | 8.0   | 6552 | 1.0090          | 0.6445   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3