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---
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-fold8
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-fold8
This model is a fine-tuned version of [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B) on the course-train-fold8 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0360
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5651 | 0.0758 | 50 | 0.3454 |
| 0.159 | 0.1516 | 100 | 0.0916 |
| 0.0775 | 0.2275 | 150 | 0.0660 |
| 0.0565 | 0.3033 | 200 | 0.0587 |
| 0.0563 | 0.3791 | 250 | 0.0594 |
| 0.0631 | 0.4549 | 300 | 0.0575 |
| 0.0677 | 0.5308 | 350 | 0.0503 |
| 0.0366 | 0.6066 | 400 | 0.0471 |
| 0.0397 | 0.6824 | 450 | 0.0430 |
| 0.0383 | 0.7582 | 500 | 0.0479 |
| 0.0508 | 0.8340 | 550 | 0.0427 |
| 0.0346 | 0.9099 | 600 | 0.0434 |
| 0.0513 | 0.9857 | 650 | 0.0444 |
| 0.0339 | 1.0615 | 700 | 0.0417 |
| 0.0296 | 1.1373 | 750 | 0.0442 |
| 0.0288 | 1.2132 | 800 | 0.0397 |
| 0.0299 | 1.2890 | 850 | 0.0421 |
| 0.0293 | 1.3648 | 900 | 0.0401 |
| 0.0278 | 1.4406 | 950 | 0.0393 |
| 0.0283 | 1.5164 | 1000 | 0.0405 |
| 0.0493 | 1.5923 | 1050 | 0.0393 |
| 0.0287 | 1.6681 | 1100 | 0.0392 |
| 0.0383 | 1.7439 | 1150 | 0.0379 |
| 0.0312 | 1.8197 | 1200 | 0.0378 |
| 0.0353 | 1.8956 | 1250 | 0.0379 |
| 0.0242 | 1.9714 | 1300 | 0.0360 |
| 0.0176 | 2.0472 | 1350 | 0.0413 |
| 0.0132 | 2.1230 | 1400 | 0.0386 |
| 0.0224 | 2.1988 | 1450 | 0.0413 |
| 0.0198 | 2.2747 | 1500 | 0.0423 |
| 0.0191 | 2.3505 | 1550 | 0.0429 |
| 0.017 | 2.4263 | 1600 | 0.0412 |
| 0.0194 | 2.5021 | 1650 | 0.0465 |
| 0.0178 | 2.5780 | 1700 | 0.0439 |
| 0.0238 | 2.6538 | 1750 | 0.0411 |
| 0.0181 | 2.7296 | 1800 | 0.0414 |
| 0.0128 | 2.8054 | 1850 | 0.0439 |
| 0.0287 | 2.8812 | 1900 | 0.0410 |
| 0.0202 | 2.9571 | 1950 | 0.0418 |
| 0.011 | 3.0329 | 2000 | 0.0430 |
| 0.005 | 3.1087 | 2050 | 0.0487 |
| 0.0045 | 3.1845 | 2100 | 0.0502 |
| 0.0072 | 3.2604 | 2150 | 0.0496 |
| 0.0098 | 3.3362 | 2200 | 0.0482 |
| 0.0089 | 3.4120 | 2250 | 0.0492 |
| 0.0072 | 3.4878 | 2300 | 0.0486 |
| 0.0116 | 3.5636 | 2350 | 0.0496 |
| 0.0094 | 3.6395 | 2400 | 0.0489 |
| 0.0055 | 3.7153 | 2450 | 0.0501 |
| 0.0095 | 3.7911 | 2500 | 0.0529 |
| 0.0113 | 3.8669 | 2550 | 0.0517 |
| 0.0042 | 3.9428 | 2600 | 0.0518 |
| 0.0021 | 4.0186 | 2650 | 0.0539 |
| 0.0027 | 4.0944 | 2700 | 0.0573 |
| 0.0017 | 4.1702 | 2750 | 0.0590 |
| 0.0033 | 4.2460 | 2800 | 0.0603 |
| 0.003 | 4.3219 | 2850 | 0.0618 |
| 0.0013 | 4.3977 | 2900 | 0.0623 |
| 0.003 | 4.4735 | 2950 | 0.0625 |
| 0.0036 | 4.5493 | 3000 | 0.0631 |
| 0.0017 | 4.6252 | 3050 | 0.0634 |
| 0.0023 | 4.7010 | 3100 | 0.0635 |
| 0.0028 | 4.7768 | 3150 | 0.0635 |
| 0.0028 | 4.8526 | 3200 | 0.0637 |
| 0.0021 | 4.9284 | 3250 | 0.0636 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |