File size: 2,477 Bytes
a2a4b31 0b41b57 a2a4b31 0b41b57 a2a4b31 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
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
should probably proofread and complete it, then remove this comment. -->
# 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 |