---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: add_BERT_no_pretrain_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      config: qqp
      split: validation
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6823893148651992
    - name: F1
      type: f1
      value: 0.4704523897892697
---

<!-- 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. -->

# add_BERT_no_pretrain_qqp

This model is a fine-tuned version of [](https://huggingface.co/) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5939
- Accuracy: 0.6824
- F1: 0.4705
- Combined Score: 0.5764

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.657         | 1.0   | 2843  | 0.6438          | 0.6490   | 0.1608 | 0.4049         |
| 0.6273        | 2.0   | 5686  | 0.6302          | 0.6443   | 0.1919 | 0.4181         |
| 0.6273        | 3.0   | 8529  | 0.6265          | 0.6527   | 0.3602 | 0.5064         |
| 0.6093        | 4.0   | 11372 | 0.5939          | 0.6824   | 0.4705 | 0.5764         |
| 0.5932        | 5.0   | 14215 | 0.5962          | 0.6802   | 0.4170 | 0.5486         |
| 0.599         | 6.0   | 17058 | 0.5981          | 0.6757   | 0.4795 | 0.5776         |
| 0.6063        | 7.0   | 19901 | 0.6511          | 0.6318   | 0.0    | 0.3159         |
| 0.6264        | 8.0   | 22744 | 0.6261          | 0.6532   | 0.2074 | 0.4303         |
| 0.6348        | 9.0   | 25587 | 0.6774          | 0.6318   | 0.0    | 0.3159         |


### Framework versions

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