transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 base_model:finetune:gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48
datasets:
- glue
language:
- en
metrics:
- matthews_correlation
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_w_init_48_ver2_cola
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE COLA
      type: glue
      config: cola
      split: validation
      args: cola
    metrics:
    - type: matthews_correlation
      value: 0.0
      name: Matthews Correlation
    - type: accuracy
      value: 0.6912751793861389
      name: Accuracy
---

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# hBERTv2_new_pretrain_w_init_48_ver2_cola

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 COLA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6181
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| 0.6346        | 1.0   | 134  | 0.6659          | 0.0                  | 0.6913   |
| 0.6202        | 2.0   | 268  | 0.6223          | 0.0                  | 0.6913   |
| 0.616         | 3.0   | 402  | 0.6202          | 0.0                  | 0.6913   |
| 0.6128        | 4.0   | 536  | 0.6181          | 0.0                  | 0.6913   |
| 0.6104        | 5.0   | 670  | 0.6182          | 0.0                  | 0.6913   |
| 0.6127        | 6.0   | 804  | 0.6263          | 0.0                  | 0.6913   |
| 0.61          | 7.0   | 938  | 0.6182          | 0.0                  | 0.6913   |
| 0.6098        | 8.0   | 1072 | 0.6181          | 0.0                  | 0.6913   |
| 0.611         | 9.0   | 1206 | 0.6205          | 0.0                  | 0.6913   |


### Framework versions

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