---
library_name: transformers
base_model: gokulsrinivasagan/bert_base_lda_5_v1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert_base_lda_5_v1_qqp
  results: []
---

<!-- 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_5_v1_qqp

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_5_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_5_v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5420
- Accuracy: 0.8560
- F1: 0.8002
- Combined Score: 0.8281

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.449         | 1.0   | 1422 | 0.3986          | 0.8140   | 0.7293 | 0.7717         |
| 0.3328        | 2.0   | 2844 | 0.3662          | 0.8379   | 0.7796 | 0.8087         |
| 0.2532        | 3.0   | 4266 | 0.3697          | 0.8430   | 0.7975 | 0.8202         |
| 0.1908        | 4.0   | 5688 | 0.4016          | 0.8528   | 0.7973 | 0.8250         |
| 0.1448        | 5.0   | 7110 | 0.4637          | 0.8542   | 0.7932 | 0.8237         |
| 0.112         | 6.0   | 8532 | 0.4905          | 0.8572   | 0.8037 | 0.8304         |
| 0.0917        | 7.0   | 9954 | 0.5420          | 0.8560   | 0.8002 | 0.8281         |


### Framework versions

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