---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_5_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6936274509803921
    - name: F1
      type: f1
      value: 0.8079877112135176
---

<!-- 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. -->

# tiny_bert_km_5_v1_mrpc

This model is a fine-tuned version of [Hartunka/tiny_bert_km_5_v1](https://huggingface.co/Hartunka/tiny_bert_km_5_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5968
- Accuracy: 0.6936
- F1: 0.8080
- Combined Score: 0.7508

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6303        | 1.0   | 15   | 0.6029          | 0.6961   | 0.8098 | 0.7529         |
| 0.5897        | 2.0   | 30   | 0.5968          | 0.6936   | 0.8080 | 0.7508         |
| 0.5512        | 3.0   | 45   | 0.6064          | 0.6936   | 0.8109 | 0.7523         |
| 0.5077        | 4.0   | 60   | 0.6256          | 0.6912   | 0.7850 | 0.7381         |
| 0.4312        | 5.0   | 75   | 0.6735          | 0.6789   | 0.7776 | 0.7283         |
| 0.3364        | 6.0   | 90   | 0.7617          | 0.6814   | 0.7751 | 0.7282         |
| 0.2516        | 7.0   | 105  | 0.8654          | 0.6373   | 0.7404 | 0.6888         |


### Framework versions

- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1