---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_tiny_lda_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_tiny_lda_20_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6985294117647058
    - name: F1
      type: f1
      value: 0.8098918083462132
---

<!-- 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_20_v1_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20_v1](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5935
- Accuracy: 0.6985
- F1: 0.8099
- Combined Score: 0.7542

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6315        | 1.0   | 15   | 0.6004          | 0.6863   | 0.8123 | 0.7493         |
| 0.6013        | 2.0   | 30   | 0.5958          | 0.6887   | 0.8037 | 0.7462         |
| 0.5707        | 3.0   | 45   | 0.5935          | 0.6985   | 0.8099 | 0.7542         |
| 0.5415        | 4.0   | 60   | 0.6069          | 0.6985   | 0.8032 | 0.7509         |
| 0.4866        | 5.0   | 75   | 0.6274          | 0.6789   | 0.7737 | 0.7263         |
| 0.397         | 6.0   | 90   | 0.7453          | 0.6985   | 0.8006 | 0.7496         |
| 0.3039        | 7.0   | 105  | 0.8151          | 0.6520   | 0.7418 | 0.6969         |
| 0.2217        | 8.0   | 120  | 0.9865          | 0.6225   | 0.7004 | 0.6615         |


### Framework versions

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