---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

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: 0.1696
- Accuracy: 0.9308
- Class 0 Precision: 0.9947
- Class 0 Recall: 0.9319
- Class 0 F1: 0.9623
- Class 0 Support: 132570
- Class 1 Precision: 0.4316
- Class 1 Recall: 0.9118
- Class 1 F1: 0.5859
- Class 1 Support: 7517

## 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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Class 0 Precision | Class 0 Recall | Class 0 F1 | Class 0 Support | Class 1 Precision | Class 1 Recall | Class 1 F1 | Class 1 Support |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|:--------------:|:----------:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|
| 0.2116        | 0.9998 | 2830 | 0.1709          | 0.9437   | 0.9334            | 0.9671         | 0.9500     | 6265            | 0.9574            | 0.9146         | 0.9355     | 5058            |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1