---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_100_v1_book_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7589503661513426
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_tiny_lda_100_v1_book_mnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_100_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1_book) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6109
- Accuracy: 0.7590

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7993        | 1.0   | 1534  | 0.6938          | 0.7060   |
| 0.6472        | 2.0   | 3068  | 0.6425          | 0.7343   |
| 0.5649        | 3.0   | 4602  | 0.6277          | 0.7479   |
| 0.4986        | 4.0   | 6136  | 0.6238          | 0.7495   |
| 0.4399        | 5.0   | 7670  | 0.6533          | 0.7545   |
| 0.3857        | 6.0   | 9204  | 0.7154          | 0.7527   |
| 0.3351        | 7.0   | 10738 | 0.7138          | 0.7572   |
| 0.2914        | 8.0   | 12272 | 0.7700          | 0.7533   |
| 0.2533        | 9.0   | 13806 | 0.8576          | 0.7496   |


### Framework versions

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