---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_rand_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_rand_5_v2_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.696078431372549
    - name: F1
      type: f1
      value: 0.7980456026058632
---

<!-- 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. -->

# distilbert_rand_5_v2_mrpc

This model is a fine-tuned version of [Hartunka/distilbert_rand_5_v2](https://huggingface.co/Hartunka/distilbert_rand_5_v2) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5870
- Accuracy: 0.6961
- F1: 0.7980
- Combined Score: 0.7471

## 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   | 0.5948          | 0.6936   | 0.8031 | 0.7484         |
| 0.5774        | 2.0   | 30   | 0.5870          | 0.6961   | 0.7980 | 0.7471         |
| 0.5136        | 3.0   | 45   | 0.6408          | 0.6936   | 0.8019 | 0.7478         |
| 0.4314        | 4.0   | 60   | 0.7090          | 0.6765   | 0.7651 | 0.7208         |
| 0.2865        | 5.0   | 75   | 0.9271          | 0.6716   | 0.7674 | 0.7195         |
| 0.1755        | 6.0   | 90   | 1.2391          | 0.6054   | 0.7046 | 0.6550         |
| 0.0968        | 7.0   | 105  | 1.5553          | 0.6348   | 0.7296 | 0.6822         |


### Framework versions

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