---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned-bert-mrpc
  results: []
---

<!-- 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. -->

# finetuned-bert-mrpc

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4725
- Accuracy: 0.8382
- F1: 0.8881

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5236        | 0.4348 | 50   | 0.4882          | 0.7647   | 0.8452 |
| 0.4277        | 0.8696 | 100  | 0.3845          | 0.8431   | 0.8940 |
| 0.2727        | 1.3043 | 150  | 0.3824          | 0.8529   | 0.8980 |
| 0.2285        | 1.7391 | 200  | 0.3646          | 0.8358   | 0.8831 |
| 0.1305        | 2.1739 | 250  | 0.3605          | 0.8652   | 0.9002 |
| 0.1193        | 2.6087 | 300  | 0.4725          | 0.8382   | 0.8881 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2