---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: modelA_1_12_2023
  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. -->

# modelA_1_12_2023

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: 0.0875
- Precision: 0.8761
- Recall: 0.8916
- F1: 0.8838
- Accuracy: 0.9756

## 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: 4.46211583196084e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0236        | 0.12  | 500  | 0.0804          | 0.8719    | 0.8856 | 0.8787 | 0.9747   |
| 0.0235        | 0.24  | 1000 | 0.0840          | 0.8461    | 0.9056 | 0.8749 | 0.9735   |
| 0.0193        | 0.37  | 1500 | 0.0869          | 0.8572    | 0.8990 | 0.8776 | 0.9745   |
| 0.0174        | 0.49  | 2000 | 0.0853          | 0.8689    | 0.8912 | 0.8799 | 0.9749   |
| 0.0136        | 0.61  | 2500 | 0.0899          | 0.8750    | 0.8923 | 0.8835 | 0.9754   |
| 0.0119        | 0.73  | 3000 | 0.0954          | 0.8685    | 0.8964 | 0.8822 | 0.9751   |
| 0.0126        | 0.85  | 3500 | 0.0919          | 0.8711    | 0.8932 | 0.8820 | 0.9754   |
| 0.0197        | 0.97  | 4000 | 0.0875          | 0.8761    | 0.8916 | 0.8838 | 0.9756   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0