Llama3-8B-SETBOX / README.md
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metadata
library_name: peft
license: llama3
base_model: meta-llama/Meta-Llama-3-8B
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Llama3-8B-SETBOX
    results: []

Llama3-8B-SETBOX

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: nan

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 50
  • training_steps: 100

Training results

Training Loss Epoch Step Validation Loss
0.0 10.0 10 nan
0.0 20.0 20 nan
0.0 30.0 30 nan
0.0 40.0 40 nan
0.0 50.0 50 nan
0.0 60.0 60 nan
0.0 70.0 70 nan
0.0 80.0 80 nan
0.0 90.0 90 nan
0.0 100.0 100 nan

Framework versions

  • PEFT 0.10.0
  • Transformers 4.46.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3