fine_tuned_mBERT – AI Model by mehdie | AlphaNeural AI

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mehdie/
fine_tuned_mBERT

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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fine_tuned_bert

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

Loss: 0.1259
F1: 0.8182
F5: 0.8326
Precision: 0.7826
Recall: 0.8571

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	F5	Precision	Recall
No log	1.0	65	0.2964	0.0	0.0	0.0	0.0
No log	2.0	130	0.2682	0.4737	0.4081	0.8182	0.3333
No log	3.0	195	0.2208	0.65	0.7421	0.4906	0.9630
No log	4.0	260	0.1924	0.7273	0.7816	0.6154	0.8889
No log	5.0	325	0.1246	0.8727	0.8788	0.8571	0.8889
No log	6.0	390	0.1142	0.8519	0.8519	0.8519	0.8519

Framework versions

Transformers 4.38.1
Pytorch 2.2.1+cu121
Datasets 2.17.0
Tokenizers 0.15.2