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_sa_GLUE_Experiment_data_aug_qqp_384
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.7994558496166213
      name: Accuracy
    - type: f1
      value: 0.7337798791699502
      name: F1
---

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# distilbert_sa_GLUE_Experiment_data_aug_qqp_384

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: 0.5363
- Accuracy: 0.7995
- F1: 0.7338
- Combined Score: 0.7666

## 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   | Accuracy | Combined Score | F1     | Validation Loss |
|:-------------:|:-----:|:------:|:--------:|:--------------:|:------:|:---------------:|
| 0.3538        | 1.0   | 29671  | 0.7995   | 0.7666         | 0.7338 | 0.5363          |
| 0.1571        | 2.0   | 59342  | 0.7215   | 0.8000         | 0.7396 | 0.7698          |
| 0.0894        | 3.0   | 89013  | 0.7922   | 0.7998         | 0.7407 | 0.7702          |
| 0.0596        | 4.0   | 118684 | 0.8829   | 0.8045         | 0.7399 | 0.7722          |
| 0.0433        | 5.0   | 148355 | 0.8505   | 0.8110         | 0.7443 | 0.7777          |
| 0.0334        | 6.0   | 178026 | 1.0843   | 0.8047         | 0.7446 | 0.7746          |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
