---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: add_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: 0.5416437854658612
---

<!-- 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. -->

# add_BERT_24_qnli

This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6883
- Accuracy: 0.5416

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6964        | 1.0   | 819   | 0.6927          | 0.5171   |
| 0.6946        | 2.0   | 1638  | 0.6927          | 0.4946   |
| 0.6936        | 3.0   | 2457  | 0.6915          | 0.5200   |
| 0.6998        | 4.0   | 3276  | 0.6902          | 0.4946   |
| 0.6925        | 5.0   | 4095  | 0.6933          | 0.5257   |
| 0.6917        | 6.0   | 4914  | 0.6893          | 0.5274   |
| 0.6914        | 7.0   | 5733  | 0.6894          | 0.5294   |
| 0.6916        | 8.0   | 6552  | 0.6888          | 0.5382   |
| 0.6913        | 9.0   | 7371  | 0.6883          | 0.5416   |
| 0.6909        | 10.0  | 8190  | 0.6892          | 0.5356   |
| 0.6914        | 11.0  | 9009  | 0.6892          | 0.5411   |
| 0.6918        | 12.0  | 9828  | 0.6907          | 0.5257   |
| 0.6911        | 13.0  | 10647 | 0.6905          | 0.5286   |
| 0.6909        | 14.0  | 11466 | 0.6896          | 0.5319   |


### Framework versions

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