---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv1_new_pretrain_48_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: 0.7058823529411765
    - name: F1
      type: f1
      value: 0.8058252427184466
---

<!-- 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_mrpc

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5714
- Accuracy: 0.7059
- F1: 0.8058
- Combined Score: 0.7559

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6764        | 1.0   | 29   | 0.5974          | 0.6887   | 0.8096 | 0.7492         |
| 0.6341        | 2.0   | 58   | 0.6032          | 0.6838   | 0.7962 | 0.7400         |
| 0.5778        | 3.0   | 87   | 0.5714          | 0.7059   | 0.8058 | 0.7559         |
| 0.4891        | 4.0   | 116  | 0.6448          | 0.7132   | 0.8104 | 0.7618         |
| 0.3469        | 5.0   | 145  | 0.8814          | 0.6593   | 0.7504 | 0.7049         |
| 0.2429        | 6.0   | 174  | 0.8431          | 0.6740   | 0.7654 | 0.7197         |
| 0.1749        | 7.0   | 203  | 1.0049          | 0.7010   | 0.7918 | 0.7464         |
| 0.1434        | 8.0   | 232  | 1.1036          | 0.6765   | 0.7634 | 0.7200         |


### Framework versions

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