transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda base_model:finetune:gokulsrinivasagan/bert_base_lda model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.845139747712095
      name: Accuracy
    - type: f1
      value: 0.7919726218559988
      name: F1
---

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# bert_base_lda_qqp

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda](https://huggingface.co/gokulsrinivasagan/bert_base_lda) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3636
- Accuracy: 0.8451
- F1: 0.7920
- Combined Score: 0.8186

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4702        | 1.0   | 1422  | 0.4119          | 0.8000   | 0.6896 | 0.7448         |
| 0.3512        | 2.0   | 2844  | 0.3694          | 0.8351   | 0.7770 | 0.8060         |
| 0.2783        | 3.0   | 4266  | 0.3636          | 0.8451   | 0.7920 | 0.8186         |
| 0.2168        | 4.0   | 5688  | 0.4190          | 0.8509   | 0.7956 | 0.8232         |
| 0.1666        | 5.0   | 7110  | 0.4654          | 0.8518   | 0.7919 | 0.8218         |
| 0.1288        | 6.0   | 8532  | 0.4836          | 0.8535   | 0.7971 | 0.8253         |
| 0.1014        | 7.0   | 9954  | 0.5922          | 0.8579   | 0.8043 | 0.8311         |
| 0.0816        | 8.0   | 11376 | 0.5662          | 0.8512   | 0.8065 | 0.8289         |


### Framework versions

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