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
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.8026465495918872
      name: Accuracy
    - type: f1
      value: 0.73920575257395
      name: F1
---

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# distilbert_sa_GLUE_Experiment_data_aug_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: 0.6240
- Accuracy: 0.8026
- F1: 0.7392
- Combined Score: 0.7709

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:--------------:|
| 0.2706        | 1.0   | 29671  | 0.6240          | 0.8026   | 0.7392 | 0.7709         |
| 0.0776        | 2.0   | 59342  | 0.8567          | 0.8033   | 0.7426 | 0.7729         |
| 0.0413        | 3.0   | 89013  | 0.9095          | 0.8077   | 0.7440 | 0.7759         |
| 0.0283        | 4.0   | 118684 | 1.0795          | 0.8087   | 0.7408 | 0.7747         |
| 0.0218        | 5.0   | 148355 | 1.2082          | 0.8097   | 0.7443 | 0.7770         |
| 0.0183        | 6.0   | 178026 | 1.2471          | 0.8032   | 0.7372 | 0.7702         |


### Framework versions

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