---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-f1-durga-muhammad
  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. -->

# bert-f1-durga-muhammad

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0079
- Accuracy: 0.999
- Precision: 0.999
- Recall: 0.999
- F1: 0.999

## 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: 4
- eval_batch_size: 8
- 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 | Precision | Recall | F1    |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:|
| 0.1978        | 0.24   | 60   | 0.1764          | 0.968    | 0.968     | 0.968  | 0.968 |
| 0.1657        | 0.48   | 120  | 0.0619          | 0.981    | 0.981     | 0.981  | 0.981 |
| 0.1155        | 0.72   | 180  | 0.0475          | 0.989    | 0.989     | 0.989  | 0.989 |
| 0.0675        | 0.96   | 240  | 0.0143          | 0.997    | 0.997     | 0.997  | 0.997 |
| 0.0009        | 1.2    | 300  | 0.0148          | 0.997    | 0.997     | 0.997  | 0.997 |
| 0.0006        | 1.44   | 360  | 0.0151          | 0.997    | 0.997     | 0.997  | 0.997 |
| 0.0267        | 1.6800 | 420  | 0.0083          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0335        | 1.92   | 480  | 0.0080          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0315        | 2.16   | 540  | 0.0073          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0056        | 2.4    | 600  | 0.0076          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0004        | 2.64   | 660  | 0.0078          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0004        | 2.88   | 720  | 0.0079          | 0.999    | 0.999     | 0.999  | 0.999 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1