---
library_name: peft
license: llama3
base_model: aaditya/Llama3-OpenBioLLM-8B
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama3-OpenBioLLM-8B-PsyCourse-fold1
  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. -->

# Llama3-OpenBioLLM-8B-PsyCourse-fold1

This model is a fine-tuned version of [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B) on the course-train-fold1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0342

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4401        | 0.0770 | 50   | 0.3166          |
| 0.1222        | 0.1539 | 100  | 0.0882          |
| 0.0887        | 0.2309 | 150  | 0.0669          |
| 0.0749        | 0.3078 | 200  | 0.0571          |
| 0.0607        | 0.3848 | 250  | 0.0536          |
| 0.0595        | 0.4617 | 300  | 0.0538          |
| 0.0569        | 0.5387 | 350  | 0.0479          |
| 0.0692        | 0.6156 | 400  | 0.0517          |
| 0.0384        | 0.6926 | 450  | 0.0476          |
| 0.0339        | 0.7695 | 500  | 0.0445          |
| 0.0515        | 0.8465 | 550  | 0.0412          |
| 0.0423        | 0.9234 | 600  | 0.0403          |
| 0.031         | 1.0004 | 650  | 0.0412          |
| 0.0415        | 1.0773 | 700  | 0.0405          |
| 0.0308        | 1.1543 | 750  | 0.0384          |
| 0.0306        | 1.2312 | 800  | 0.0376          |
| 0.0376        | 1.3082 | 850  | 0.0391          |
| 0.024         | 1.3851 | 900  | 0.0384          |
| 0.0406        | 1.4621 | 950  | 0.0392          |
| 0.0398        | 1.5391 | 1000 | 0.0376          |
| 0.0325        | 1.6160 | 1050 | 0.0356          |
| 0.0396        | 1.6930 | 1100 | 0.0394          |
| 0.0266        | 1.7699 | 1150 | 0.0388          |
| 0.023         | 1.8469 | 1200 | 0.0392          |
| 0.0315        | 1.9238 | 1250 | 0.0389          |
| 0.0238        | 2.0008 | 1300 | 0.0342          |
| 0.0189        | 2.0777 | 1350 | 0.0361          |
| 0.0293        | 2.1547 | 1400 | 0.0367          |
| 0.0128        | 2.2316 | 1450 | 0.0420          |
| 0.0195        | 2.3086 | 1500 | 0.0385          |
| 0.0174        | 2.3855 | 1550 | 0.0383          |
| 0.0143        | 2.4625 | 1600 | 0.0415          |
| 0.0249        | 2.5394 | 1650 | 0.0404          |
| 0.0195        | 2.6164 | 1700 | 0.0383          |
| 0.0266        | 2.6933 | 1750 | 0.0376          |
| 0.0216        | 2.7703 | 1800 | 0.0365          |
| 0.0236        | 2.8472 | 1850 | 0.0366          |
| 0.0198        | 2.9242 | 1900 | 0.0369          |
| 0.0311        | 3.0012 | 1950 | 0.0370          |
| 0.0088        | 3.0781 | 2000 | 0.0424          |
| 0.0126        | 3.1551 | 2050 | 0.0467          |
| 0.0085        | 3.2320 | 2100 | 0.0463          |
| 0.0083        | 3.3090 | 2150 | 0.0453          |
| 0.0164        | 3.3859 | 2200 | 0.0470          |
| 0.0115        | 3.4629 | 2250 | 0.0465          |
| 0.0134        | 3.5398 | 2300 | 0.0469          |
| 0.0052        | 3.6168 | 2350 | 0.0470          |
| 0.0104        | 3.6937 | 2400 | 0.0448          |
| 0.0075        | 3.7707 | 2450 | 0.0459          |
| 0.0068        | 3.8476 | 2500 | 0.0485          |
| 0.0089        | 3.9246 | 2550 | 0.0494          |
| 0.0091        | 4.0015 | 2600 | 0.0476          |
| 0.0021        | 4.0785 | 2650 | 0.0498          |
| 0.0061        | 4.1554 | 2700 | 0.0529          |
| 0.0011        | 4.2324 | 2750 | 0.0541          |
| 0.0025        | 4.3093 | 2800 | 0.0549          |
| 0.0029        | 4.3863 | 2850 | 0.0560          |
| 0.0027        | 4.4633 | 2900 | 0.0570          |
| 0.0017        | 4.5402 | 2950 | 0.0572          |
| 0.0019        | 4.6172 | 3000 | 0.0574          |
| 0.005         | 4.6941 | 3050 | 0.0575          |
| 0.0033        | 4.7711 | 3100 | 0.0573          |
| 0.005         | 4.8480 | 3150 | 0.0576          |
| 0.0019        | 4.9250 | 3200 | 0.0575          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3