---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_tiny_lda_100_v1_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7035191212367778
---

<!-- 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_tiny_lda_100_v1_mnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_100_v1) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6947
- Accuracy: 0.7035

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9642        | 1.0   | 1534  | 0.8561          | 0.6113   |
| 0.8313        | 2.0   | 3068  | 0.7812          | 0.6520   |
| 0.757         | 3.0   | 4602  | 0.7462          | 0.6743   |
| 0.6957        | 4.0   | 6136  | 0.7300          | 0.6888   |
| 0.6441        | 5.0   | 7670  | 0.7240          | 0.6961   |
| 0.5971        | 6.0   | 9204  | 0.7375          | 0.6971   |
| 0.5545        | 7.0   | 10738 | 0.7476          | 0.7041   |
| 0.5132        | 8.0   | 12272 | 0.7632          | 0.7020   |
| 0.4736        | 9.0   | 13806 | 0.8263          | 0.7010   |
| 0.4355        | 10.0  | 15340 | 0.8340          | 0.7018   |


### Framework versions

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