---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: hBERTv1_new_pretrain_w_init__wnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: wnli
      split: validation
      args: wnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.43661971830985913
---

<!-- 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_new_pretrain_w_init__wnli

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7009
- Accuracy: 0.4366

## 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: 0.0005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 12.3688       | 1.0   | 5    | 6.2236          | 0.5634   |
| 3.5093        | 2.0   | 10   | 0.7491          | 0.4366   |
| 1.9112        | 3.0   | 15   | 2.5146          | 0.5634   |
| 1.4995        | 4.0   | 20   | 1.8104          | 0.4366   |
| 1.3047        | 5.0   | 25   | 0.6936          | 0.5634   |
| 1.4685        | 6.0   | 30   | 0.7440          | 0.5634   |
| 0.924         | 7.0   | 35   | 1.1066          | 0.4366   |
| 0.8423        | 8.0   | 40   | 0.8221          | 0.4366   |
| 0.8166        | 9.0   | 45   | 0.6855          | 0.5634   |
| 0.7552        | 10.0  | 50   | 0.7181          | 0.5634   |
| 0.7515        | 11.0  | 55   | 0.6951          | 0.5634   |
| 0.7127        | 12.0  | 60   | 0.7140          | 0.4366   |
| 0.7112        | 13.0  | 65   | 0.6901          | 0.5634   |
| 0.6976        | 14.0  | 70   | 0.7009          | 0.4366   |


### Framework versions

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