---
base_model: meta-llama/Llama-3.1-8B
library_name: peft
license: llama3.1
tags:
- question-answering
- QA
- text-generation
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-medquad-V2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3.1-8B-medquad-V2

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the MedQuAD: Ben-Abacha and Demner-Fushman (2019) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8959

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 12
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2503        | 0.1462 | 10   | 1.1359          |
| 1.1182        | 0.2923 | 20   | 1.0199          |
| 1.0864        | 0.4385 | 30   | 0.9856          |
| 0.9031        | 0.5847 | 40   | 0.9681          |
| 1.0773        | 0.7308 | 50   | 0.9499          |
| 0.9575        | 0.8770 | 60   | 0.9427          |
| 0.9768        | 1.0231 | 70   | 0.9452          |
| 0.9673        | 1.1693 | 80   | 0.9264          |
| 0.8541        | 1.3155 | 90   | 0.9282          |
| 0.9772        | 1.4616 | 100  | 0.9180          |
| 0.8427        | 1.6078 | 110  | 0.9211          |
| 0.9317        | 1.7540 | 120  | 0.9142          |
| 0.9498        | 1.9001 | 130  | 0.9011          |
| 0.8412        | 2.0463 | 140  | 0.9036          |
| 0.899         | 2.1924 | 150  | 0.9031          |
| 0.7488        | 2.3386 | 160  | 0.8990          |
| 0.8824        | 2.4848 | 170  | 0.9033          |
| 0.8334        | 2.6309 | 180  | 0.8959          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0