llama-3.1-8b-instruct_LBox-10x2-clustered-fallback-plus-shared-lora-moe

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llama-3.1-8b-instruct_LBox-10x2-clustered-fallback-plus-shared-lora-moe

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9706
• Router Supervised Loss: 0.1246
• Router Valid Mass Loss: 0.1246
• Router Slot Loss: 0.0
• Router Load Balance Loss: 5.2259
• Router Z Loss: 5.9282

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: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• total_eval_batch_size: 2
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 0.03
• num_epochs: 5.0

Training results

Framework versions

• Transformers 5.9.0
• Pytorch 2.11.0+cu130
• Datasets 4.4.1
• Tokenizers 0.22.2