---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_rand_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_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: 0.696078431372549
    - name: F1
      type: f1
      value: 0.8050314465408805
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert_rand_50_v1_mrpc

This model is a fine-tuned version of [Hartunka/distilbert_rand_50_v1](https://huggingface.co/Hartunka/distilbert_rand_50_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5905
- Accuracy: 0.6961
- F1: 0.8050
- Combined Score: 0.7506

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6355        | 1.0   | 15   | 0.6204          | 0.6887   | 0.7894 | 0.7391         |
| 0.5874        | 2.0   | 30   | 0.5905          | 0.6961   | 0.8050 | 0.7506         |
| 0.5207        | 3.0   | 45   | 0.6095          | 0.6985   | 0.7960 | 0.7473         |
| 0.4109        | 4.0   | 60   | 0.7317          | 0.6618   | 0.75   | 0.7059         |
| 0.2525        | 5.0   | 75   | 0.9530          | 0.6740   | 0.7542 | 0.7141         |
| 0.1571        | 6.0   | 90   | 1.0934          | 0.6593   | 0.7477 | 0.7035         |
| 0.1027        | 7.0   | 105  | 1.2743          | 0.6593   | 0.7440 | 0.7017         |


### Framework versions

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