transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda_book base_model:finetune:gokulsrinivasagan/bert_base_lda_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_book_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.8882018303240168
      name: Accuracy
    - type: f1
      value: 0.8573772560898649
      name: F1
---

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# bert_base_lda_book_qqp

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_book) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2583
- Accuracy: 0.8882
- F1: 0.8574
- Combined Score: 0.8728

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3436        | 1.0   | 1422 | 0.2806          | 0.8777   | 0.8326 | 0.8552         |
| 0.2299        | 2.0   | 2844 | 0.2583          | 0.8882   | 0.8574 | 0.8728         |
| 0.1622        | 3.0   | 4266 | 0.2690          | 0.8982   | 0.8630 | 0.8806         |
| 0.1135        | 4.0   | 5688 | 0.2749          | 0.9002   | 0.8627 | 0.8815         |
| 0.0836        | 5.0   | 7110 | 0.3357          | 0.8989   | 0.8640 | 0.8814         |
| 0.065         | 6.0   | 8532 | 0.3486          | 0.9000   | 0.8637 | 0.8818         |
| 0.0525        | 7.0   | 9954 | 0.4290          | 0.8978   | 0.8663 | 0.8821         |


### Framework versions

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