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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-fold5
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-fold5
This model is a fine-tuned version of [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B) on the course-train-fold5 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5262 | 0.0758 | 50 | 0.3222 |
| 0.0888 | 0.1517 | 100 | 0.0871 |
| 0.0821 | 0.2275 | 150 | 0.0828 |
| 0.0718 | 0.3033 | 200 | 0.0627 |
| 0.0622 | 0.3791 | 250 | 0.0543 |
| 0.0509 | 0.4550 | 300 | 0.0504 |
| 0.0576 | 0.5308 | 350 | 0.0506 |
| 0.066 | 0.6066 | 400 | 0.0472 |
| 0.0593 | 0.6825 | 450 | 0.0450 |
| 0.0316 | 0.7583 | 500 | 0.0445 |
| 0.0318 | 0.8341 | 550 | 0.0472 |
| 0.0436 | 0.9100 | 600 | 0.0449 |
| 0.0454 | 0.9858 | 650 | 0.0416 |
| 0.0339 | 1.0616 | 700 | 0.0424 |
| 0.0369 | 1.1374 | 750 | 0.0448 |
| 0.034 | 1.2133 | 800 | 0.0374 |
| 0.0332 | 1.2891 | 850 | 0.0419 |
| 0.029 | 1.3649 | 900 | 0.0428 |
| 0.031 | 1.4408 | 950 | 0.0432 |
| 0.0353 | 1.5166 | 1000 | 0.0388 |
| 0.0278 | 1.5924 | 1050 | 0.0380 |
| 0.0261 | 1.6682 | 1100 | 0.0366 |
| 0.0294 | 1.7441 | 1150 | 0.0390 |
| 0.0337 | 1.8199 | 1200 | 0.0366 |
| 0.0359 | 1.8957 | 1250 | 0.0350 |
| 0.0358 | 1.9716 | 1300 | 0.0363 |
| 0.0233 | 2.0474 | 1350 | 0.0363 |
| 0.0157 | 2.1232 | 1400 | 0.0363 |
| 0.0227 | 2.1991 | 1450 | 0.0357 |
| 0.018 | 2.2749 | 1500 | 0.0389 |
| 0.0237 | 2.3507 | 1550 | 0.0354 |
| 0.025 | 2.4265 | 1600 | 0.0365 |
| 0.015 | 2.5024 | 1650 | 0.0392 |
| 0.0265 | 2.5782 | 1700 | 0.0360 |
| 0.0181 | 2.6540 | 1750 | 0.0368 |
| 0.0228 | 2.7299 | 1800 | 0.0380 |
| 0.0224 | 2.8057 | 1850 | 0.0366 |
| 0.0162 | 2.8815 | 1900 | 0.0356 |
| 0.0284 | 2.9573 | 1950 | 0.0349 |
| 0.0069 | 3.0332 | 2000 | 0.0351 |
| 0.0065 | 3.1090 | 2050 | 0.0394 |
| 0.0069 | 3.1848 | 2100 | 0.0438 |
| 0.006 | 3.2607 | 2150 | 0.0446 |
| 0.0088 | 3.3365 | 2200 | 0.0436 |
| 0.0056 | 3.4123 | 2250 | 0.0424 |
| 0.0086 | 3.4882 | 2300 | 0.0445 |
| 0.0058 | 3.5640 | 2350 | 0.0438 |
| 0.0092 | 3.6398 | 2400 | 0.0426 |
| 0.0082 | 3.7156 | 2450 | 0.0433 |
| 0.01 | 3.7915 | 2500 | 0.0422 |
| 0.0082 | 3.8673 | 2550 | 0.0426 |
| 0.012 | 3.9431 | 2600 | 0.0433 |
| 0.0054 | 4.0190 | 2650 | 0.0437 |
| 0.0037 | 4.0948 | 2700 | 0.0452 |
| 0.0049 | 4.1706 | 2750 | 0.0474 |
| 0.0024 | 4.2464 | 2800 | 0.0492 |
| 0.0023 | 4.3223 | 2850 | 0.0507 |
| 0.0048 | 4.3981 | 2900 | 0.0512 |
| 0.0073 | 4.4739 | 2950 | 0.0514 |
| 0.0014 | 4.5498 | 3000 | 0.0518 |
| 0.0021 | 4.6256 | 3050 | 0.0521 |
| 0.0043 | 4.7014 | 3100 | 0.0525 |
| 0.005 | 4.7773 | 3150 | 0.0528 |
| 0.0021 | 4.8531 | 3200 | 0.0531 |
| 0.0032 | 4.9289 | 3250 | 0.0529 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |