metadata

license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
  - generated_from_trainer
metrics:
  - recall
  - accuracy
model-index:
  - name: multibert_1210seed25
    results: []

multibert_1210seed25

This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4453
Precisions: 0.8647
Recall: 0.8314
F-measure: 0.8459
Accuracy: 0.9141

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: 7.5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 25
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 14

Training results

Training Loss	Epoch	Step	Validation Loss	Precisions	Recall	F-measure	Accuracy
0.6013	1.0	236	0.4080	0.8974	0.6857	0.7273	0.8736
0.319	2.0	472	0.3621	0.8338	0.7306	0.7317	0.8875
0.1929	3.0	708	0.3823	0.8020	0.7680	0.7761	0.9022
0.1389	4.0	944	0.4353	0.8400	0.7742	0.7990	0.9003
0.0958	5.0	1180	0.4348	0.8726	0.7547	0.7971	0.9011
0.0676	6.0	1416	0.4453	0.8647	0.8314	0.8459	0.9141
0.0506	7.0	1652	0.5222	0.8555	0.8013	0.8253	0.9100
0.0315	8.0	1888	0.5192	0.8700	0.7873	0.8187	0.9108
0.0229	9.0	2124	0.5977	0.8402	0.7839	0.8079	0.9062
0.0149	10.0	2360	0.6061	0.8622	0.8069	0.8305	0.9131
0.0122	11.0	2596	0.5894	0.8419	0.7702	0.7983	0.9085
0.0065	12.0	2832	0.6120	0.8514	0.7700	0.8021	0.9089
0.0039	13.0	3068	0.6434	0.8437	0.7646	0.7965	0.9055
0.003	14.0	3304	0.6391	0.8403	0.7670	0.7973	0.9062

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1