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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama-3-8B-Instruct-Medical-QLoRA
This model is a adapter for [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/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 |