---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda_5_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_lda_5_v1_book_qnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QNLI
      type: glue
      args: qnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8544755628775398
---

<!-- 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_book_qnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_5_v1_book) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3441
- Accuracy: 0.8545

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4848        | 1.0   | 410  | 0.3843          | 0.8343   |
| 0.3412        | 2.0   | 820  | 0.3441          | 0.8545   |
| 0.2379        | 3.0   | 1230 | 0.3484          | 0.8567   |
| 0.1558        | 4.0   | 1640 | 0.4954          | 0.8389   |
| 0.1041        | 5.0   | 2050 | 0.5006          | 0.8376   |
| 0.0824        | 6.0   | 2460 | 0.5768          | 0.8532   |
| 0.0601        | 7.0   | 2870 | 0.5504          | 0.8547   |


### Framework versions

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