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mbert-am-100k-finetuned-II – AI Model by Bonnief | AlphaNeural AI
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Bonnief
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mbert-am-100k-finetuned-II
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transformers
tensorboard
safetensors
bert
fill-mask
generated_from_trainer
google-bert/bert-base-multilingual-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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mbert-am-100k-finetuned-II
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: nan
Accuracy: 0.2069
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
