---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_48_KD_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: 0.7156862745098039
    - name: F1
      type: f1
      value: 0.8104575163398692
---

<!-- 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_48_KD_w_init_mrpc

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48_KD_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48_KD_wt_init) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5878
- Accuracy: 0.7157
- F1: 0.8105
- Combined Score: 0.7631

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6514        | 1.0   | 29   | 0.6205          | 0.6887   | 0.8146 | 0.7517         |
| 0.619         | 2.0   | 58   | 0.6165          | 0.6618   | 0.7366 | 0.6992         |
| 0.6208        | 3.0   | 87   | 0.5878          | 0.7157   | 0.8105 | 0.7631         |
| 0.578         | 4.0   | 116  | 0.5952          | 0.7132   | 0.7986 | 0.7559         |
| 0.5612        | 5.0   | 145  | 0.5910          | 0.6936   | 0.7899 | 0.7418         |
| 0.4844        | 6.0   | 174  | 0.6261          | 0.6520   | 0.7290 | 0.6905         |
| 0.4281        | 7.0   | 203  | 0.6146          | 0.7010   | 0.7932 | 0.7471         |
| 0.3919        | 8.0   | 232  | 0.7273          | 0.6838   | 0.7795 | 0.7317         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3