---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_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: 0.5053999633900788
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hBERTv1_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: 0.6931
- 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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7059        | 1.0   | 1092  | 0.7004          | 0.5054   |
| 0.6948        | 2.0   | 2184  | 0.6938          | 0.4946   |
| 0.6939        | 3.0   | 3276  | 0.6932          | 0.5054   |
| 0.6936        | 4.0   | 4368  | 0.6931          | 0.5054   |
| 0.6934        | 5.0   | 5460  | 0.6931          | 0.5054   |
| 0.6936        | 6.0   | 6552  | 0.6931          | 0.5054   |
| 0.6933        | 7.0   | 7644  | 0.6931          | 0.5054   |
| 0.6933        | 8.0   | 8736  | 0.6931          | 0.5054   |
| 0.6934        | 9.0   | 9828  | 0.6934          | 0.5054   |
| 0.6933        | 10.0  | 10920 | 0.6931          | 0.5054   |
| 0.6932        | 11.0  | 12012 | 0.6933          | 0.4946   |
| 0.6932        | 12.0  | 13104 | 0.6931          | 0.5054   |
| 0.6933        | 13.0  | 14196 | 0.6931          | 0.5054   |


### Framework versions

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