transformers pytorch tensorboard distilbert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_add_GLUE_Experiment_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      config: qqp
      split: validation
      args: qqp
    metrics:
    - type: accuracy
      value: 0.8319564679693298
      name: Accuracy
    - type: f1
      value: 0.7639168809507263
      name: F1
---

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# distilbert_add_GLUE_Experiment_qqp

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4050
- Accuracy: 0.8320
- F1: 0.7639
- Combined Score: 0.7979

## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5406        | 1.0   | 1422  | 0.4844          | 0.7648   | 0.6276 | 0.6962         |
| 0.4161        | 2.0   | 2844  | 0.4451          | 0.8044   | 0.6939 | 0.7491         |
| 0.3079        | 3.0   | 4266  | 0.4050          | 0.8320   | 0.7639 | 0.7979         |
| 0.2338        | 4.0   | 5688  | 0.4633          | 0.8388   | 0.7715 | 0.8052         |
| 0.1801        | 5.0   | 7110  | 0.5597          | 0.8346   | 0.7489 | 0.7918         |
| 0.1433        | 6.0   | 8532  | 0.5641          | 0.8460   | 0.7774 | 0.8117         |
| 0.1155        | 7.0   | 9954  | 0.5940          | 0.8481   | 0.7889 | 0.8185         |
| 0.0963        | 8.0   | 11376 | 0.6896          | 0.8438   | 0.7670 | 0.8054         |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
