---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_lda_5_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8815978233984665
    - name: F1
      type: f1
      value: 0.8448046685038093
---

<!-- 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_5_v1_qqp

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2878
- Accuracy: 0.8816
- F1: 0.8448
- Combined Score: 0.8632

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.376         | 1.0   | 1422  | 0.3084          | 0.8608   | 0.8144 | 0.8376         |
| 0.267         | 2.0   | 2844  | 0.2947          | 0.8694   | 0.8362 | 0.8528         |
| 0.2049        | 3.0   | 4266  | 0.2878          | 0.8816   | 0.8448 | 0.8632         |
| 0.1541        | 4.0   | 5688  | 0.3070          | 0.8845   | 0.8391 | 0.8618         |
| 0.1166        | 5.0   | 7110  | 0.3458          | 0.8864   | 0.8441 | 0.8653         |
| 0.0894        | 6.0   | 8532  | 0.3844          | 0.8853   | 0.8449 | 0.8651         |
| 0.0719        | 7.0   | 9954  | 0.4213          | 0.8848   | 0.8482 | 0.8665         |
| 0.0579        | 8.0   | 11376 | 0.4257          | 0.8842   | 0.8468 | 0.8655         |


### Framework versions

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