---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: hBERTv2_new_no_pretrain_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: 0.6838235294117647
    - name: F1
      type: f1
      value: 0.7895595432300163
---

<!-- 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. -->

# hBERTv2_new_no_pretrain_mrpc

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5914
- Accuracy: 0.6838
- F1: 0.7896
- Combined Score: 0.7367

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6685        | 1.0   | 29   | 0.6107          | 0.6838   | 0.8122 | 0.7480         |
| 0.6337        | 2.0   | 58   | 0.5914          | 0.6838   | 0.7896 | 0.7367         |
| 0.529         | 3.0   | 87   | 0.6385          | 0.6642   | 0.7705 | 0.7174         |
| 0.4182        | 4.0   | 116  | 0.6619          | 0.6985   | 0.8051 | 0.7518         |
| 0.3095        | 5.0   | 145  | 1.0040          | 0.6471   | 0.7568 | 0.7019         |
| 0.2219        | 6.0   | 174  | 0.9458          | 0.6225   | 0.7094 | 0.6660         |
| 0.1813        | 7.0   | 203  | 1.1249          | 0.6838   | 0.7868 | 0.7353         |


### Framework versions

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