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mbert-ti-100k-finetuned – AI Model by Bonnief | AlphaNeural AI

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Bonnief/
mbert-ti-100k-finetuned

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generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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mbert-ti-100k-finetuned

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

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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
lr_scheduler_warmup_steps: 1000
training_steps: 100000
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.53.0.dev0
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1