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metadata
license: llama3
library_name: peft
tags:
  - trl
  - sft
  - generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
  - name: results
    results: []
datasets:
  - medalpaca/medical_meadow_medical_flashcards
  - medalpaca/medical_meadow_wikidoc
  - medalpaca/medical_meadow_wikidoc_patient_information
  - medalpaca/medical_meadow_medqa
  - lavita/MedQuAD
  - Mreeb/Dermatology-Question-Answer-Dataset-For-Fine-Tuning
language:
  - en

Llama-3-8B-Instruct-Medical-QLoRA

This model is a adapter for meta-llama/Meta-Llama-3-8B-Instruct, finetuned on a subset of given datasets. It achieves the following results on the evaluation set:

  • Loss: 1.1646

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: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
2.217 0.0591 20 1.5876
1.4821 0.1182 40 1.3649
1.3217 0.1773 60 1.2501
1.2392 0.2363 80 1.2201
1.1963 0.2954 100 1.2075
1.1829 0.3545 120 1.1997
1.2229 0.4136 140 1.1917
1.2016 0.4727 160 1.1868
1.1753 0.5318 180 1.1831
1.216 0.5908 200 1.1790
1.1831 0.6499 220 1.1761
1.1941 0.7090 240 1.1730
1.2566 0.7681 260 1.1702
1.1908 0.8272 280 1.1681
1.1586 0.8863 300 1.1665
1.1956 0.9453 320 1.1646

Framework versions

  • PEFT 0.11.0
  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1