---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: ernie-finetuned-qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9156566905763047
    - name: F1
      type: f1
      value: 0.8860522622468757
---

<!-- 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. -->

# ernie-finetuned-qqp

This model is a fine-tuned version of [nghuyong/ernie-2.0-en](https://huggingface.co/nghuyong/ernie-2.0-en) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4381
- Accuracy: 0.9157
- F1: 0.8861

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
| 0.2522        | 1.0   | 22741  | 0.2505          | 0.8997   | 0.8633 |
| 0.1903        | 2.0   | 45482  | 0.2645          | 0.9071   | 0.8761 |
| 0.1599        | 3.0   | 68223  | 0.2986          | 0.9115   | 0.8816 |
| 0.1214        | 4.0   | 90964  | 0.3640          | 0.9133   | 0.8828 |
| 0.0809        | 5.0   | 113705 | 0.4381          | 0.9157   | 0.8861 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
