---
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-fold4
  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-fold4

This model is a fine-tuned version of [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B) on the course-train-fold4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0349

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.4799        | 0.0763 | 50   | 0.2933          |
| 0.1053        | 0.1527 | 100  | 0.0766          |
| 0.0594        | 0.2290 | 150  | 0.0722          |
| 0.0586        | 0.3053 | 200  | 0.0537          |
| 0.066         | 0.3816 | 250  | 0.0550          |
| 0.0553        | 0.4580 | 300  | 0.0551          |
| 0.0468        | 0.5343 | 350  | 0.0476          |
| 0.0515        | 0.6106 | 400  | 0.0481          |
| 0.0562        | 0.6870 | 450  | 0.0466          |
| 0.0347        | 0.7633 | 500  | 0.0401          |
| 0.0417        | 0.8396 | 550  | 0.0408          |
| 0.0466        | 0.9159 | 600  | 0.0393          |
| 0.0346        | 0.9923 | 650  | 0.0404          |
| 0.035         | 1.0686 | 700  | 0.0389          |
| 0.0408        | 1.1449 | 750  | 0.0390          |
| 0.0324        | 1.2213 | 800  | 0.0427          |
| 0.0331        | 1.2976 | 850  | 0.0382          |
| 0.0335        | 1.3739 | 900  | 0.0433          |
| 0.034         | 1.4502 | 950  | 0.0374          |
| 0.0253        | 1.5266 | 1000 | 0.0399          |
| 0.0299        | 1.6029 | 1050 | 0.0382          |
| 0.0534        | 1.6792 | 1100 | 0.0424          |
| 0.0318        | 1.7556 | 1150 | 0.0402          |
| 0.0484        | 1.8319 | 1200 | 0.0385          |
| 0.0263        | 1.9082 | 1250 | 0.0355          |
| 0.0329        | 1.9845 | 1300 | 0.0349          |
| 0.0171        | 2.0609 | 1350 | 0.0365          |
| 0.0204        | 2.1372 | 1400 | 0.0374          |
| 0.0248        | 2.2135 | 1450 | 0.0413          |
| 0.0132        | 2.2899 | 1500 | 0.0397          |
| 0.0152        | 2.3662 | 1550 | 0.0383          |
| 0.0222        | 2.4425 | 1600 | 0.0387          |
| 0.0187        | 2.5188 | 1650 | 0.0374          |
| 0.0177        | 2.5952 | 1700 | 0.0415          |
| 0.0164        | 2.6715 | 1750 | 0.0380          |
| 0.0212        | 2.7478 | 1800 | 0.0395          |
| 0.0248        | 2.8242 | 1850 | 0.0357          |
| 0.0187        | 2.9005 | 1900 | 0.0384          |
| 0.0315        | 2.9768 | 1950 | 0.0372          |
| 0.006         | 3.0531 | 2000 | 0.0423          |
| 0.0077        | 3.1295 | 2050 | 0.0459          |
| 0.0073        | 3.2058 | 2100 | 0.0493          |
| 0.0096        | 3.2821 | 2150 | 0.0523          |
| 0.0086        | 3.3585 | 2200 | 0.0449          |
| 0.0057        | 3.4348 | 2250 | 0.0469          |
| 0.0098        | 3.5111 | 2300 | 0.0460          |
| 0.0086        | 3.5874 | 2350 | 0.0493          |
| 0.0073        | 3.6638 | 2400 | 0.0471          |
| 0.0086        | 3.7401 | 2450 | 0.0468          |
| 0.0079        | 3.8164 | 2500 | 0.0455          |
| 0.0042        | 3.8928 | 2550 | 0.0473          |
| 0.0088        | 3.9691 | 2600 | 0.0474          |
| 0.004         | 4.0454 | 2650 | 0.0474          |
| 0.0033        | 4.1217 | 2700 | 0.0500          |
| 0.0009        | 4.1981 | 2750 | 0.0520          |
| 0.0021        | 4.2744 | 2800 | 0.0532          |
| 0.0042        | 4.3507 | 2850 | 0.0546          |
| 0.0017        | 4.4271 | 2900 | 0.0566          |
| 0.002         | 4.5034 | 2950 | 0.0577          |
| 0.0021        | 4.5797 | 3000 | 0.0583          |
| 0.0017        | 4.6560 | 3050 | 0.0585          |
| 0.0036        | 4.7324 | 3100 | 0.0587          |
| 0.0021        | 4.8087 | 3150 | 0.0588          |
| 0.0028        | 4.8850 | 3200 | 0.0588          |
| 0.0021        | 4.9614 | 3250 | 0.0588          |


### Framework versions

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