---
language:
- en
base_model: Hartunka/tiny_bert_rand_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_rand_50_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6813725490196079
    - name: F1
      type: f1
      value: 0.7936507936507936
---

<!-- 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_50_v1_mrpc

This model is a fine-tuned version of [Hartunka/tiny_bert_rand_50_v1](https://huggingface.co/Hartunka/tiny_bert_rand_50_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5949
- Accuracy: 0.6814
- F1: 0.7937
- Combined Score: 0.7375

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6286        | 1.0   | 15   | 0.6045          | 0.6863   | 0.8019 | 0.7441         |
| 0.5948        | 2.0   | 30   | 0.5950          | 0.6985   | 0.8087 | 0.7536         |
| 0.556         | 3.0   | 45   | 0.5949          | 0.6814   | 0.7937 | 0.7375         |
| 0.5107        | 4.0   | 60   | 0.6383          | 0.7108   | 0.7958 | 0.7533         |
| 0.4193        | 5.0   | 75   | 0.6820          | 0.6495   | 0.7366 | 0.6931         |
| 0.3479        | 6.0   | 90   | 0.8077          | 0.7034   | 0.8    | 0.7517         |
| 0.2647        | 7.0   | 105  | 0.8842          | 0.6838   | 0.7795 | 0.7317         |
| 0.1929        | 8.0   | 120  | 1.0427          | 0.6814   | 0.7833 | 0.7324         |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1