---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_48_emb_com_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: 0.7083333333333334
    - name: F1
      type: f1
      value: 0.8172043010752688
---

<!-- 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_emb_com_mrpc

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5831
- Accuracy: 0.7083
- F1: 0.8172
- Combined Score: 0.7628

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6776        | 1.0   | 29   | 0.6052          | 0.7010   | 0.8146 | 0.7578         |
| 0.6271        | 2.0   | 58   | 0.6112          | 0.6961   | 0.8025 | 0.7493         |
| 0.58          | 3.0   | 87   | 0.5831          | 0.7083   | 0.8172 | 0.7628         |
| 0.5494        | 4.0   | 116  | 0.6458          | 0.7010   | 0.8094 | 0.7552         |
| 0.5148        | 5.0   | 145  | 0.6067          | 0.6838   | 0.7882 | 0.7360         |
| 0.4573        | 6.0   | 174  | 0.6267          | 0.6863   | 0.7935 | 0.7399         |
| 0.395         | 7.0   | 203  | 0.7897          | 0.6275   | 0.7295 | 0.6785         |
| 0.3102        | 8.0   | 232  | 0.9040          | 0.6593   | 0.7599 | 0.7096         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3