---
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-V3
  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-V3

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: 0.9213

## 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: 20
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 12
- total_train_batch_size: 240
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6067        | 0.1826 | 10   | 1.5411          |
| 1.5616        | 0.3653 | 20   | 1.2822          |
| 1.2619        | 0.5479 | 30   | 1.1497          |
| 1.1906        | 0.7306 | 40   | 1.0566          |
| 1.0764        | 0.9132 | 50   | 0.9903          |
| 0.9496        | 1.0959 | 60   | 0.9758          |
| 1.0131        | 1.2785 | 70   | 0.9630          |
| 0.9908        | 1.4612 | 80   | 0.9502          |
| 0.9786        | 1.6438 | 90   | 0.9434          |
| 0.9182        | 1.8265 | 100  | 0.9366          |
| 0.9621        | 2.0091 | 110  | 0.9341          |
| 0.9724        | 2.1918 | 120  | 0.9254          |
| 0.8955        | 2.3744 | 130  | 0.9213          |


### Framework versions

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