---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_lda_20_v1_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6318327974276527
    - name: F1
      type: f1
      value: 0.0
---

<!-- 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. -->

# bert_base_lda_20_v1_qqp

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_20_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_20_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6573
- Accuracy: 0.6318
- F1: 0.0
- Combined Score: 0.3159

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---:|:--------------:|
| 0.6686        | 1.0   | 1422  | 0.6588          | 0.6318   | 0.0 | 0.3159         |
| 0.659         | 2.0   | 2844  | 0.6578          | 0.6318   | 0.0 | 0.3159         |
| 0.6586        | 3.0   | 4266  | 0.6582          | 0.6318   | 0.0 | 0.3159         |
| 0.6586        | 4.0   | 5688  | 0.6574          | 0.6318   | 0.0 | 0.3159         |
| 0.6585        | 5.0   | 7110  | 0.6576          | 0.6318   | 0.0 | 0.3159         |
| 0.6587        | 6.0   | 8532  | 0.6580          | 0.6318   | 0.0 | 0.3159         |
| 0.6584        | 7.0   | 9954  | 0.6573          | 0.6318   | 0.0 | 0.3159         |
| 0.6585        | 8.0   | 11376 | 0.6573          | 0.6318   | 0.0 | 0.3159         |
| 0.6586        | 9.0   | 12798 | 0.6578          | 0.6318   | 0.0 | 0.3159         |
| 0.6586        | 10.0  | 14220 | 0.6578          | 0.6318   | 0.0 | 0.3159         |
| 0.6586        | 11.0  | 15642 | 0.6580          | 0.6318   | 0.0 | 0.3159         |
| 0.662         | 12.0  | 17064 | 0.6576          | 0.6318   | 0.0 | 0.3159         |


### Framework versions

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