metadata

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
    results: []

bert-f1-durga-muhammad

This model is a fine-tuned version of 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