---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: benchmark-finetuned-bert
  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. -->

# benchmark-finetuned-bert

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4553
- Accuracy: 0.8267
- F1: 0.8270

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.803         | 1.0   | 48   | 0.6463          | 0.6997   | 0.6460 |
| 0.5508        | 2.0   | 96   | 0.5141          | 0.8042   | 0.8051 |
| 0.4111        | 3.0   | 144  | 0.4553          | 0.8267   | 0.8270 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1