---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      config: mnli
      split: validation_matched
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.3522172497965826
---

<!-- 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_mnli

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 MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0982
- Accuracy: 0.3522

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1001        | 1.0   | 1534  | 1.0994          | 0.3182   |
| 1.0988        | 2.0   | 3068  | 1.0990          | 0.3182   |
| 1.0987        | 3.0   | 4602  | 1.0992          | 0.3274   |
| 1.0987        | 4.0   | 6136  | 1.0986          | 0.3274   |
| 1.0987        | 5.0   | 7670  | 1.0985          | 0.3545   |
| 1.0986        | 6.0   | 9204  | 1.0987          | 0.3274   |
| 1.105         | 7.0   | 10738 | 1.0986          | 0.3274   |
| 1.1045        | 8.0   | 12272 | 1.0986          | 0.3182   |
| 1.0988        | 9.0   | 13806 | 1.0983          | 0.3274   |
| 1.0987        | 10.0  | 15340 | 1.0987          | 0.3182   |
| 1.0987        | 11.0  | 16874 | 1.0991          | 0.3182   |
| 1.0986        | 12.0  | 18408 | 1.0986          | 0.3545   |
| 1.0986        | 13.0  | 19942 | 1.0982          | 0.3545   |
| 1.0986        | 14.0  | 21476 | 1.0989          | 0.3545   |
| 1.0986        | 15.0  | 23010 | 1.0987          | 0.3182   |
| 1.0986        | 16.0  | 24544 | 1.0986          | 0.3545   |
| 1.0986        | 17.0  | 26078 | 1.0986          | 0.3545   |
| 1.0986        | 18.0  | 27612 | 1.0983          | 0.3182   |


### Framework versions

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