---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_rand_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_rand_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: 0.6936274509803921
    - name: F1
      type: f1
      value: 0.8073959938366718
---

<!-- 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_rand_20_v1_mrpc

This model is a fine-tuned version of [Hartunka/tiny_bert_rand_20_v1](https://huggingface.co/Hartunka/tiny_bert_rand_20_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5944
- Accuracy: 0.6936
- F1: 0.8074
- Combined Score: 0.7505

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6234        | 1.0   | 15   | 0.6028          | 0.6961   | 0.8050 | 0.7506         |
| 0.5729        | 2.0   | 30   | 0.5944          | 0.6936   | 0.8074 | 0.7505         |
| 0.5187        | 3.0   | 45   | 0.6136          | 0.6985   | 0.8093 | 0.7539         |
| 0.4667        | 4.0   | 60   | 0.6242          | 0.7059   | 0.8052 | 0.7555         |
| 0.372         | 5.0   | 75   | 0.6987          | 0.6765   | 0.7676 | 0.7220         |
| 0.2679        | 6.0   | 90   | 0.8146          | 0.6863   | 0.7739 | 0.7301         |
| 0.173         | 7.0   | 105  | 0.9934          | 0.6593   | 0.7495 | 0.7044         |


### Framework versions

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