metadata
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: []
Llama-3.1-8B-medquad-V2
This model is a fine-tuned version of 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