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mmc_roberta_500000_fr – AI Model by Kyungjin-Kim | AlphaNeural AI
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mmc_roberta_500000_fr
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transformers
safetensors
roberta
fill-mask
generated_from_trainer
autotrain_compatible
endpoints_compatible
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mmc_roberta_500000_fr
This model is a fine-tuned version of
on an unknown dataset.
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: 0.00025
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 32
optimizer: Use 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: 5000
training_steps: 100000
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3
