---
license: apache-2.0
base_model: bert-base-cased
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-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4442
- Accuracy: 0.8456
- F1: 0.8927

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5676        | 1.0   | 230  | 0.4019          | 0.8309   | 0.8844 |
| 0.3437        | 2.0   | 460  | 0.3926          | 0.8407   | 0.8896 |
| 0.1913        | 3.0   | 690  | 0.4442          | 0.8456   | 0.8927 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.1
- Datasets 2.19.1
- Tokenizers 0.19.1