transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_lda_20_v1_book base_model:finetune:gokulsrinivasagan/distilbert_lda_20_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_lda_20_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_20_v1_book_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.8854563442987881
      name: Accuracy
    - type: f1
      value: 0.8475692044369837
      name: F1
---

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# distilbert_lda_20_v1_book_qqp

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_20_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_20_v1_book) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2665
- Accuracy: 0.8855
- F1: 0.8476
- Combined Score: 0.8665

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3665        | 1.0   | 1422 | 0.2946          | 0.8691   | 0.8240 | 0.8466         |
| 0.2538        | 2.0   | 2844 | 0.2665          | 0.8855   | 0.8476 | 0.8665         |
| 0.1867        | 3.0   | 4266 | 0.2858          | 0.8875   | 0.8532 | 0.8703         |
| 0.1356        | 4.0   | 5688 | 0.3081          | 0.8911   | 0.8477 | 0.8694         |
| 0.0999        | 5.0   | 7110 | 0.3504          | 0.8922   | 0.8554 | 0.8738         |
| 0.0769        | 6.0   | 8532 | 0.3767          | 0.8896   | 0.8550 | 0.8723         |
| 0.0597        | 7.0   | 9954 | 0.3907          | 0.8910   | 0.8556 | 0.8733         |


### Framework versions

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