---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FPB_finetuned_v1
  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. -->

# FPB_finetuned_v1

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: 0.4649
- Accuracy: 0.9303
- F1: 0.9303
- Precision: 0.9303
- Recall: 0.9303

## 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: 0.0001
- 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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7905        | 1.0   | 97   | 0.6913          | 0.7504   | 0.7471 | 0.7458    | 0.7504 |
| 0.3516        | 2.0   | 194  | 0.3914          | 0.8476   | 0.8480 | 0.8517    | 0.8476 |
| 0.2545        | 3.0   | 291  | 0.3302          | 0.8882   | 0.8870 | 0.8911    | 0.8882 |
| 0.1225        | 4.0   | 388  | 0.3488          | 0.8723   | 0.8730 | 0.8801    | 0.8723 |
| 0.0674        | 5.0   | 485  | 0.3910          | 0.8970   | 0.8961 | 0.8963    | 0.8970 |
| 0.0458        | 6.0   | 582  | 0.4545          | 0.9028   | 0.9022 | 0.9036    | 0.9028 |
| 0.0963        | 7.0   | 679  | 0.3467          | 0.9100   | 0.9100 | 0.9104    | 0.9100 |
| 0.0781        | 8.0   | 776  | 0.4528          | 0.8999   | 0.8991 | 0.8996    | 0.8999 |
| 0.0961        | 9.0   | 873  | 0.3966          | 0.9042   | 0.9049 | 0.9091    | 0.9042 |
| 0.0643        | 10.0  | 970  | 0.3486          | 0.9158   | 0.9159 | 0.9160    | 0.9158 |
| 0.0521        | 11.0  | 1067 | 0.5745          | 0.8955   | 0.8931 | 0.9030    | 0.8955 |
| 0.0162        | 12.0  | 1164 | 0.4968          | 0.9042   | 0.9047 | 0.9070    | 0.9042 |
| 0.0106        | 13.0  | 1261 | 0.4925          | 0.9158   | 0.9161 | 0.9171    | 0.9158 |
| 0.0056        | 14.0  | 1358 | 0.5128          | 0.9129   | 0.9126 | 0.9149    | 0.9129 |
| 0.0116        | 15.0  | 1455 | 0.4791          | 0.9202   | 0.9199 | 0.9197    | 0.9202 |
| 0.0004        | 16.0  | 1552 | 0.4417          | 0.9216   | 0.9214 | 0.9218    | 0.9216 |
| 0.0121        | 17.0  | 1649 | 0.4378          | 0.9202   | 0.9199 | 0.9205    | 0.9202 |
| 0.0003        | 18.0  | 1746 | 0.4624          | 0.9245   | 0.9245 | 0.9247    | 0.9245 |
| 0.0001        | 19.0  | 1843 | 0.4697          | 0.9274   | 0.9275 | 0.9277    | 0.9274 |
| 0.0001        | 20.0  | 1940 | 0.4649          | 0.9303   | 0.9303 | 0.9303    | 0.9303 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2