transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_book base_model:finetune:gokulsrinivasagan/bert_tiny_lda_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_book_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.8785060598565422
      name: Accuracy
    - type: f1
      value: 0.8395714938924815
      name: F1
---

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# bert_tiny_lda_book_qqp

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_book) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2838
- Accuracy: 0.8785
- F1: 0.8396
- Combined Score: 0.8590

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4015        | 1.0   | 1422  | 0.3287          | 0.8523   | 0.8041 | 0.8282         |
| 0.2957        | 2.0   | 2844  | 0.3002          | 0.8676   | 0.8285 | 0.8481         |
| 0.2403        | 3.0   | 4266  | 0.2838          | 0.8785   | 0.8396 | 0.8590         |
| 0.1973        | 4.0   | 5688  | 0.2938          | 0.8807   | 0.8350 | 0.8579         |
| 0.1599        | 5.0   | 7110  | 0.3001          | 0.8830   | 0.8459 | 0.8644         |
| 0.1313        | 6.0   | 8532  | 0.3227          | 0.8831   | 0.8467 | 0.8649         |
| 0.108         | 7.0   | 9954  | 0.3420          | 0.8842   | 0.8475 | 0.8659         |
| 0.0902        | 8.0   | 11376 | 0.3866          | 0.8824   | 0.8466 | 0.8645         |


### Framework versions

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