mBERT_sa_cv_9_fold2 – AI Model by DiederikMartens | AlphaNeural AI

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DiederikMartens/
mBERT_sa_cv_9_fold2

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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mBERT_sa_cv_9_fold2

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: 0.5117
F1: 0.5612

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: 4.47e-05
train_batch_size: 16
eval_batch_size: 32
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	F1
No log	1.0	325	0.6121	0.2931
0.6217	2.0	650	0.4958	0.4713
0.6217	3.0	975	0.5117	0.5612

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1