---
language:
- en
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
- accuracy
model-index:
- name: hBERTv1_new_pretrain_w_init_48_ver2_cola
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE COLA
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - name: Matthews Correlation
      type: matthews_correlation
      value: 0.0
    - name: Accuracy
      type: accuracy
      value: 0.6912751793861389
---

<!-- 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_48_ver2_cola

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6179
- Matthews Correlation: 0.0
- Accuracy: 0.6913

## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6277        | 1.0   | 134  | 0.6457          | 0.0                  | 0.6913   |
| 0.6178        | 2.0   | 268  | 0.6240          | 0.0                  | 0.6913   |
| 0.6152        | 3.0   | 402  | 0.6201          | 0.0                  | 0.6913   |
| 0.6138        | 4.0   | 536  | 0.6181          | 0.0                  | 0.6913   |
| 0.6111        | 5.0   | 670  | 0.6181          | 0.0                  | 0.6913   |
| 0.6122        | 6.0   | 804  | 0.6232          | 0.0                  | 0.6913   |
| 0.611         | 7.0   | 938  | 0.6179          | 0.0                  | 0.6913   |
| 0.6087        | 8.0   | 1072 | 0.6182          | 0.0                  | 0.6913   |
| 0.6112        | 9.0   | 1206 | 0.6226          | 0.0                  | 0.6913   |
| 0.6116        | 10.0  | 1340 | 0.6210          | 0.0                  | 0.6913   |
| 0.6091        | 11.0  | 1474 | 0.6194          | 0.0                  | 0.6913   |
| 0.6087        | 12.0  | 1608 | 0.6184          | 0.0                  | 0.6913   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1