---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_lda_100_v1_book_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8875092752906257
    - name: F1
      type: f1
      value: 0.850019786307875
---

<!-- 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. -->

# distilbert_lda_100_v1_book_qqp

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_100_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1_book) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2688
- Accuracy: 0.8875
- F1: 0.8500
- Combined Score: 0.8688

## 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 OptimizerNames.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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3709        | 1.0   | 1422  | 0.3001          | 0.8678   | 0.8193 | 0.8436         |
| 0.2573        | 2.0   | 2844  | 0.2834          | 0.8762   | 0.8426 | 0.8594         |
| 0.1922        | 3.0   | 4266  | 0.2688          | 0.8875   | 0.8500 | 0.8688         |
| 0.1411        | 4.0   | 5688  | 0.3129          | 0.8910   | 0.8506 | 0.8708         |
| 0.105         | 5.0   | 7110  | 0.3257          | 0.8932   | 0.8563 | 0.8748         |
| 0.0794        | 6.0   | 8532  | 0.3696          | 0.8901   | 0.8546 | 0.8723         |
| 0.0646        | 7.0   | 9954  | 0.3887          | 0.8889   | 0.8537 | 0.8713         |
| 0.0528        | 8.0   | 11376 | 0.4293          | 0.8906   | 0.8565 | 0.8735         |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1