---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_rand_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert_base_rand_20_v1_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7132352941176471
    - name: F1
      type: f1
      value: 0.7958115183246073
---

<!-- 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. -->

# bert_base_rand_20_v1_mrpc

This model is a fine-tuned version of [Hartunka/bert_base_rand_20_v1](https://huggingface.co/Hartunka/bert_base_rand_20_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5873
- Accuracy: 0.7132
- F1: 0.7958
- Combined Score: 0.7545

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6376        | 1.0   | 15   | 0.5900          | 0.6912   | 0.8006 | 0.7459         |
| 0.5782        | 2.0   | 30   | 0.5873          | 0.7132   | 0.7958 | 0.7545         |
| 0.5004        | 3.0   | 45   | 0.5992          | 0.7157   | 0.7986 | 0.7571         |
| 0.3709        | 4.0   | 60   | 0.7209          | 0.6936   | 0.7723 | 0.7330         |
| 0.2326        | 5.0   | 75   | 0.9645          | 0.6814   | 0.7610 | 0.7212         |
| 0.1352        | 6.0   | 90   | 1.1715          | 0.6789   | 0.7690 | 0.7239         |
| 0.0961        | 7.0   | 105  | 1.2892          | 0.6618   | 0.7579 | 0.7098         |


### Framework versions

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