---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-512_A-8
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_uncased_L-4_H-512_A-8_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8914172644076181
    - name: F1
      type: f1
      value: 0.8539295933985492
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert_uncased_L-4_H-512_A-8_qqp

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2574
- Accuracy: 0.8914
- F1: 0.8539
- Combined Score: 0.8727

## 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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3551        | 1.0   | 1422  | 0.2993          | 0.8693   | 0.8179 | 0.8436         |
| 0.2662        | 2.0   | 2844  | 0.2663          | 0.8842   | 0.8492 | 0.8667         |
| 0.217         | 3.0   | 4266  | 0.2574          | 0.8914   | 0.8539 | 0.8727         |
| 0.179         | 4.0   | 5688  | 0.2646          | 0.8937   | 0.8550 | 0.8744         |
| 0.1487        | 5.0   | 7110  | 0.2920          | 0.8938   | 0.8582 | 0.8760         |
| 0.1228        | 6.0   | 8532  | 0.2971          | 0.8936   | 0.8587 | 0.8762         |
| 0.1042        | 7.0   | 9954  | 0.3390          | 0.8916   | 0.8577 | 0.8746         |
| 0.0882        | 8.0   | 11376 | 0.3568          | 0.8931   | 0.8604 | 0.8768         |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3