---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_km_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: 0.6862745098039216
    - name: F1
      type: f1
      value: 0.7935483870967742
---

<!-- 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_km_5_v2_mrpc

This model is a fine-tuned version of [Hartunka/distilbert_km_5_v2](https://huggingface.co/Hartunka/distilbert_km_5_v2) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5962
- Accuracy: 0.6863
- F1: 0.7935
- Combined Score: 0.7399

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6185        | 1.0   | 15   | 0.6003          | 0.6789   | 0.7904 | 0.7347         |
| 0.5391        | 2.0   | 30   | 0.5962          | 0.6863   | 0.7935 | 0.7399         |
| 0.4435        | 3.0   | 45   | 0.6493          | 0.6961   | 0.7947 | 0.7454         |
| 0.3126        | 4.0   | 60   | 0.7969          | 0.6765   | 0.7747 | 0.7256         |
| 0.1757        | 5.0   | 75   | 1.0385          | 0.6544   | 0.7504 | 0.7024         |
| 0.0809        | 6.0   | 90   | 1.3466          | 0.6838   | 0.7795 | 0.7317         |
| 0.0458        | 7.0   | 105  | 1.5137          | 0.6838   | 0.7749 | 0.7293         |


### Framework versions

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