transformers pytorch distilbert text-classification generated_from_trainer dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: glue-qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.9033391046252782
      name: Accuracy
    - type: f1
      value: 0.8703384207033842
      name: F1
---

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# glue-qqp

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4798
- Accuracy: 0.9033
- F1: 0.8703

## 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     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
| 0.2779        | 1.0   | 22741  | 0.2697          | 0.8871   | 0.8494 |
| 0.2183        | 2.0   | 45482  | 0.2651          | 0.8966   | 0.8634 |
| 0.1635        | 3.0   | 68223  | 0.3116          | 0.9013   | 0.8685 |
| 0.1312        | 4.0   | 90964  | 0.4102          | 0.9030   | 0.8694 |
| 0.0802        | 5.0   | 113705 | 0.4798          | 0.9033   | 0.8703 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.11.6
