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me5_large_inst_full_os_96_24 – AI Model by Ehsanl | AlphaNeural AI
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Ehsanl
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me5_large_inst_full_os_96_24
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transformers
safetensors
xlm-roberta
feature-extraction
generated_from_trainer
intfloat/multilingual-e5-large-instruct
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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me5_large_inst_full_os_96_24
This model is a fine-tuned version of
intfloat/multilingual-e5-large-instruct
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: 8e-06
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
total_train_batch_size: 32
total_eval_batch_size: 32
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_ratio: 0.2
num_epochs: 1.0
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.54.1
Pytorch 2.7.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4
