transformers pytorch tensorboard bert 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: sa_BERT_no_pretrain_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: 0.7934207271827851
      name: Accuracy
    - type: f1
      value: 0.6836123948783999
      name: F1
---

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# sa_BERT_no_pretrain_qqp

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4355
- Accuracy: 0.7934
- F1: 0.6836
- Combined Score: 0.7385

## 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: 4e-05
- train_batch_size: 96
- eval_batch_size: 96
- 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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.5241        | 1.0   | 3791  | 0.4947          | 0.7638   | 0.6550 | 0.7094         |
| 0.4527        | 2.0   | 7582  | 0.4524          | 0.7853   | 0.7027 | 0.7440         |
| 0.404         | 3.0   | 11373 | 0.4355          | 0.7934   | 0.6836 | 0.7385         |
| 0.3675        | 4.0   | 15164 | 0.4407          | 0.8038   | 0.7438 | 0.7738         |
| 0.3315        | 5.0   | 18955 | 0.4426          | 0.8060   | 0.7368 | 0.7714         |
| 0.3031        | 6.0   | 22746 | 0.4437          | 0.8067   | 0.7444 | 0.7755         |
| 0.2747        | 7.0   | 26537 | 0.4359          | 0.8046   | 0.7523 | 0.7785         |
| 0.2441        | 8.0   | 30328 | 0.4718          | 0.8074   | 0.7547 | 0.7811         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
