---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_20_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_lda_20_v1_book_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7720588235294118
    - name: F1
      type: f1
      value: 0.8312159709618874
---

<!-- 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_book_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_20_v1_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_20_v1_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5004
- Accuracy: 0.7721
- F1: 0.8312
- Combined Score: 0.8016

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6176        | 1.0   | 15   | 0.5701          | 0.7034   | 0.8180 | 0.7607         |
| 0.5574        | 2.0   | 30   | 0.5202          | 0.7377   | 0.8271 | 0.7824         |
| 0.4414        | 3.0   | 45   | 0.5004          | 0.7721   | 0.8312 | 0.8016         |
| 0.3089        | 4.0   | 60   | 0.6028          | 0.7598   | 0.8444 | 0.8021         |
| 0.1931        | 5.0   | 75   | 0.6150          | 0.8162   | 0.8727 | 0.8444         |
| 0.1366        | 6.0   | 90   | 0.7471          | 0.7794   | 0.8548 | 0.8171         |
| 0.0839        | 7.0   | 105  | 0.7483          | 0.7990   | 0.8656 | 0.8323         |
| 0.0409        | 8.0   | 120  | 0.9451          | 0.7892   | 0.8604 | 0.8248         |


### Framework versions

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