---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_100_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: 0.7475490196078431
    - name: F1
      type: f1
      value: 0.8303130148270182
---

<!-- 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_book_mrpc

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 MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5396
- Accuracy: 0.7475
- F1: 0.8303
- Combined Score: 0.7889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.62          | 1.0   | 15   | 0.5966          | 0.6740   | 0.7892 | 0.7316         |
| 0.5856        | 2.0   | 30   | 0.5702          | 0.7010   | 0.8129 | 0.7569         |
| 0.5467        | 3.0   | 45   | 0.5471          | 0.7279   | 0.8195 | 0.7737         |
| 0.4866        | 4.0   | 60   | 0.5721          | 0.7426   | 0.8331 | 0.7879         |
| 0.4174        | 5.0   | 75   | 0.5396          | 0.7475   | 0.8303 | 0.7889         |
| 0.3418        | 6.0   | 90   | 0.5986          | 0.75     | 0.8211 | 0.7855         |
| 0.2528        | 7.0   | 105  | 0.6746          | 0.6985   | 0.7593 | 0.7289         |
| 0.1784        | 8.0   | 120  | 0.6922          | 0.7304   | 0.7925 | 0.7614         |
| 0.1522        | 9.0   | 135  | 0.7651          | 0.7574   | 0.8395 | 0.7984         |
| 0.1123        | 10.0  | 150  | 0.7805          | 0.7574   | 0.8308 | 0.7941         |


### Framework versions

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