AIKIA_0.6_OFFENSIVE_BERT_MULTILINGUAL1 – AI Model by christinacdl | AlphaNeural AI

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christinacdl/
AIKIA_0.6_OFFENSIVE_BERT_MULTILINGUAL1

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text-classification

generated_from_trainer

christinacdl/AIKIA_Offensive_Greek

autotrain_compatible

endpoints_compatible

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AIKIA_0.6_OFFENSIVE_BERT_MULTILINGUAL1

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: 0.7624
Macro F1: 0.7128
Micro F1: 0.7601
Accuracy: 0.7601

Performance on test set:

Accuracy: 0.7973856209150327
F1 score: 0.7760745870386702
Precision: 0.775117096128912
Recall : 0.7770859985785359
Matthews Correlation Coefficient: 0.5521995845956664
Precision of each class: [0.84854564 0.70168856]
Recall of each class: [0.84179104 0.71238095]
F1 score of each class: [0.84515485 0.70699433]

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Micro F1	Accuracy
No log	1.0	338	0.5701	0.7024	0.7122	0.7122
0.5808	2.0	676	0.5888	0.7221	0.7528	0.7528
0.4027	3.0	1014	0.6163	0.7265	0.7528	0.7528
0.4027	4.0	1352	0.7624	0.7128	0.7601	0.7601

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3