---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: sa_BERT_24_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: 0.6218195130880468
---

<!-- 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. -->

# sa_BERT_24_qnli

This model is a fine-tuned version of [gokuls/bert_base_24](https://huggingface.co/gokuls/bert_base_24) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6492
- Accuracy: 0.6218

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6745        | 1.0   | 1092 | 0.6686          | 0.5817   |
| 0.6338        | 2.0   | 2184 | 0.6492          | 0.6218   |
| 0.5909        | 3.0   | 3276 | 0.6560          | 0.6251   |
| 0.5407        | 4.0   | 4368 | 0.7246          | 0.6269   |
| 0.4732        | 5.0   | 5460 | 0.6612          | 0.6421   |
| 0.3999        | 6.0   | 6552 | 0.7506          | 0.6410   |
| 0.3203        | 7.0   | 7644 | 0.9162          | 0.6306   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3