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

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: 0.0001
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:|
| 0.0245        | 1.0   | 42   | 0.0241          | 0.995    | 0.995     | 0.995  | 0.995 |
| 0.0032        | 2.0   | 84   | 0.0081          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0011        | 3.0   | 126  | 0.0075          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0008        | 4.0   | 168  | 0.0068          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0006        | 5.0   | 210  | 0.0078          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0012        | 6.0   | 252  | 0.0063          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0022        | 7.0   | 294  | 0.0015          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0004        | 8.0   | 336  | 0.0031          | 0.999    | 0.999     | 0.999  | 0.999 |
| 0.0003        | 9.0   | 378  | 0.0002          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0002        | 10.0  | 420  | 0.0002          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0002        | 11.0  | 462  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0002        | 12.0  | 504  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0002        | 13.0  | 546  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0001        | 14.0  | 588  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0001        | 15.0  | 630  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0001        | 16.0  | 672  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |
| 0.0001        | 17.0  | 714  | 0.0001          | 1.0      | 1.0       | 1.0    | 1.0   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1