relianceV2 / README.md
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metadata
library_name: peft
license: other
base_model: unsloth/Llama-3.2-3B-Instruct
tags:
  - llama-factory
  - lora
  - unsloth
  - generated_from_trainer
model-index:
  - name: llm3br256
    results: []

llm3br256

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the relianceV2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0118

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_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: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5.0

Training results

Training Loss Epoch Step Validation Loss
0.0395 0.2424 5 0.0433
0.0324 0.4848 10 0.0300
0.024 0.7273 15 0.0244
0.0189 0.9697 20 0.0212
0.0171 1.2303 25 0.0190
0.0146 1.4727 30 0.0173
0.0144 1.7152 35 0.0161
0.0104 1.9576 40 0.0155
0.0143 2.2182 45 0.0152
0.0117 2.4606 50 0.0141
0.015 2.7030 55 0.0136
0.0092 2.9455 60 0.0131
0.008 3.2061 65 0.0127
0.0109 3.4485 70 0.0125
0.0085 3.6909 75 0.0122
0.0089 3.9333 80 0.0120
0.0074 4.1939 85 0.0118
0.0074 4.4364 90 0.0118
0.0066 4.6788 95 0.0118
0.0065 4.9212 100 0.0118

Framework versions

  • PEFT 0.12.0
  • Transformers 4.46.1
  • Pytorch 2.4.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3