---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_10_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_10_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7009803921568627
    - name: F1
      type: f1
      value: 0.8032258064516129
---

<!-- 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_10_v1_mrpc

This model is a fine-tuned version of [Hartunka/tiny_bert_km_10_v1](https://huggingface.co/Hartunka/tiny_bert_km_10_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5893
- Accuracy: 0.7010
- F1: 0.8032
- Combined Score: 0.7521

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6324        | 1.0   | 15   | 0.6063          | 0.7108   | 0.8223 | 0.7665         |
| 0.596         | 2.0   | 30   | 0.5934          | 0.7034   | 0.8191 | 0.7613         |
| 0.5663        | 3.0   | 45   | 0.5923          | 0.7083   | 0.8200 | 0.7642         |
| 0.5449        | 4.0   | 60   | 0.5893          | 0.7010   | 0.8032 | 0.7521         |
| 0.4957        | 5.0   | 75   | 0.6304          | 0.6569   | 0.75   | 0.7034         |
| 0.4356        | 6.0   | 90   | 0.6516          | 0.6936   | 0.7871 | 0.7403         |
| 0.3509        | 7.0   | 105  | 0.7439          | 0.6887   | 0.7908 | 0.7397         |
| 0.2548        | 8.0   | 120  | 0.8600          | 0.6618   | 0.7553 | 0.7085         |
| 0.1693        | 9.0   | 135  | 1.0956          | 0.6225   | 0.7148 | 0.6687         |


### Framework versions

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