---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_w_init__mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6862745098039216
    - name: F1
      type: f1
      value: 0.7894736842105262
---

<!-- 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__mrpc

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 MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6082
- Accuracy: 0.6863
- F1: 0.7895
- Combined Score: 0.7379

## 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 | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.7111        | 1.0   | 29   | 0.6564          | 0.6838   | 0.8122 | 0.7480         |
| 0.6641        | 2.0   | 58   | 0.6160          | 0.6838   | 0.8122 | 0.7480         |
| 0.6156        | 3.0   | 87   | 0.6354          | 0.6838   | 0.8122 | 0.7480         |
| 0.5817        | 4.0   | 116  | 0.6082          | 0.6863   | 0.7895 | 0.7379         |
| 0.5091        | 5.0   | 145  | 0.7812          | 0.5074   | 0.5157 | 0.5115         |
| 0.3973        | 6.0   | 174  | 0.7949          | 0.6544   | 0.7565 | 0.7054         |
| 0.2966        | 7.0   | 203  | 1.0388          | 0.6078   | 0.6887 | 0.6483         |
| 0.2024        | 8.0   | 232  | 1.0065          | 0.6201   | 0.7124 | 0.6663         |
| 0.1621        | 9.0   | 261  | 1.3076          | 0.5735   | 0.6575 | 0.6155         |


### Framework versions

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