llama3-1-8b-xquad-lora-tr

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tr

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

• Loss: 0.3097
• Accuracy: 0.9227
• Mcq Accuracy: 0.8151

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: 0.00015
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.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: 0.1
• num_epochs: 3.0

Training results

Framework versions

• PEFT 0.18.1
• Transformers 5.2.0
• Pytorch 2.10.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2