---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_rand_10_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_rand_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: 0.6666666666666666
    - name: F1
      type: f1
      value: 0.7748344370860927
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert_rand_10_v1_mrpc

This model is a fine-tuned version of [Hartunka/distilbert_rand_10_v1](https://huggingface.co/Hartunka/distilbert_rand_10_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5884
- Accuracy: 0.6667
- F1: 0.7748
- Combined Score: 0.7208

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6309        | 1.0   | 15   | 0.5976          | 0.6936   | 0.8013 | 0.7474         |
| 0.5756        | 2.0   | 30   | 0.5884          | 0.6667   | 0.7748 | 0.7208         |
| 0.507         | 3.0   | 45   | 0.6164          | 0.6985   | 0.7967 | 0.7476         |
| 0.4021        | 4.0   | 60   | 0.7436          | 0.6838   | 0.7733 | 0.7286         |
| 0.2627        | 5.0   | 75   | 0.9784          | 0.6127   | 0.7008 | 0.6568         |
| 0.1522        | 6.0   | 90   | 1.2598          | 0.6397   | 0.7252 | 0.6825         |
| 0.0925        | 7.0   | 105  | 1.4431          | 0.6544   | 0.7556 | 0.7050         |


### Framework versions

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