---
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-fold10
  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-fold10

This model is a fine-tuned version of [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B) on the course-train-fold10 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0347

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5221        | 0.0770 | 50   | 0.3092          |
| 0.0971        | 0.1539 | 100  | 0.0860          |
| 0.0873        | 0.2309 | 150  | 0.0607          |
| 0.0616        | 0.3078 | 200  | 0.0565          |
| 0.071         | 0.3848 | 250  | 0.0542          |
| 0.0615        | 0.4618 | 300  | 0.0497          |
| 0.0538        | 0.5387 | 350  | 0.0468          |
| 0.0532        | 0.6157 | 400  | 0.0462          |
| 0.0501        | 0.6926 | 450  | 0.0482          |
| 0.0575        | 0.7696 | 500  | 0.0422          |
| 0.0418        | 0.8466 | 550  | 0.0440          |
| 0.048         | 0.9235 | 600  | 0.0398          |
| 0.0559        | 1.0005 | 650  | 0.0397          |
| 0.0358        | 1.0774 | 700  | 0.0431          |
| 0.0277        | 1.1544 | 750  | 0.0392          |
| 0.029         | 1.2314 | 800  | 0.0376          |
| 0.0283        | 1.3083 | 850  | 0.0383          |
| 0.035         | 1.3853 | 900  | 0.0371          |
| 0.0367        | 1.4622 | 950  | 0.0373          |
| 0.0272        | 1.5392 | 1000 | 0.0428          |
| 0.0435        | 1.6162 | 1050 | 0.0367          |
| 0.0379        | 1.6931 | 1100 | 0.0368          |
| 0.0296        | 1.7701 | 1150 | 0.0378          |
| 0.0423        | 1.8470 | 1200 | 0.0377          |
| 0.0389        | 1.9240 | 1250 | 0.0347          |
| 0.0349        | 2.0010 | 1300 | 0.0378          |
| 0.0191        | 2.0779 | 1350 | 0.0376          |
| 0.0252        | 2.1549 | 1400 | 0.0371          |
| 0.016         | 2.2318 | 1450 | 0.0381          |
| 0.0211        | 2.3088 | 1500 | 0.0362          |
| 0.0223        | 2.3858 | 1550 | 0.0355          |
| 0.0227        | 2.4627 | 1600 | 0.0385          |
| 0.0268        | 2.5397 | 1650 | 0.0354          |
| 0.0267        | 2.6166 | 1700 | 0.0349          |
| 0.0158        | 2.6936 | 1750 | 0.0352          |
| 0.0186        | 2.7706 | 1800 | 0.0384          |
| 0.0155        | 2.8475 | 1850 | 0.0401          |
| 0.0158        | 2.9245 | 1900 | 0.0365          |
| 0.0185        | 3.0014 | 1950 | 0.0362          |
| 0.0103        | 3.0784 | 2000 | 0.0401          |
| 0.0111        | 3.1554 | 2050 | 0.0402          |
| 0.0105        | 3.2323 | 2100 | 0.0448          |
| 0.0077        | 3.3093 | 2150 | 0.0435          |
| 0.0078        | 3.3862 | 2200 | 0.0476          |
| 0.0072        | 3.4632 | 2250 | 0.0457          |
| 0.0118        | 3.5402 | 2300 | 0.0452          |
| 0.0107        | 3.6171 | 2350 | 0.0448          |
| 0.01          | 3.6941 | 2400 | 0.0478          |
| 0.0092        | 3.7710 | 2450 | 0.0471          |
| 0.0166        | 3.8480 | 2500 | 0.0437          |
| 0.0048        | 3.9250 | 2550 | 0.0444          |
| 0.0057        | 4.0019 | 2600 | 0.0454          |
| 0.0033        | 4.0789 | 2650 | 0.0484          |
| 0.0032        | 4.1558 | 2700 | 0.0500          |
| 0.005         | 4.2328 | 2750 | 0.0527          |
| 0.004         | 4.3098 | 2800 | 0.0546          |
| 0.0034        | 4.3867 | 2850 | 0.0554          |
| 0.0023        | 4.4637 | 2900 | 0.0560          |
| 0.0027        | 4.5406 | 2950 | 0.0564          |
| 0.0025        | 4.6176 | 3000 | 0.0563          |
| 0.0054        | 4.6946 | 3050 | 0.0568          |
| 0.0016        | 4.7715 | 3100 | 0.0569          |
| 0.0024        | 4.8485 | 3150 | 0.0567          |
| 0.0018        | 4.9254 | 3200 | 0.0568          |


### Framework versions

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