claim-spotter-multilingual – AI Model by vaibhavbhajanka | AlphaNeural AI

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vaibhavbhajanka/
claim-spotter-multilingual

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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claim-spotter-multilingual

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

Loss: 0.3139
F1: 0.8309

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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.4728	1.0	830	0.4621	0.7407
0.3577	2.0	1660	0.3139	0.8309

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1