transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_w_init_48_qnli
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QNLI
      type: glue
      config: qnli
      split: validation
      args: qnli
    metrics:
    - type: accuracy
      value: 0.7867472084935018
      name: Accuracy
---

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# hBERTv2_new_pretrain_w_init_48_qnli

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4725
- Accuracy: 0.7867

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6735        | 1.0   | 819  | 0.6754          | 0.5689   |
| 0.6251        | 2.0   | 1638 | 0.5403          | 0.7346   |
| 0.4993        | 3.0   | 2457 | 0.4725          | 0.7867   |
| 0.4195        | 4.0   | 3276 | 0.5245          | 0.7681   |
| 0.3542        | 5.0   | 4095 | 0.5522          | 0.7569   |
| 0.2952        | 6.0   | 4914 | 0.5402          | 0.7785   |
| 0.2422        | 7.0   | 5733 | 0.6739          | 0.7578   |
| 0.2024        | 8.0   | 6552 | 0.5727          | 0.7851   |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
