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---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-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. -->
# Llama-3.1-8B-Instruct-PsyCourse-fold5
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the course-train-fold5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0336
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.6474 | 0.0758 | 50 | 0.4173 |
| 0.0891 | 0.1517 | 100 | 0.0932 |
| 0.0787 | 0.2275 | 150 | 0.0860 |
| 0.059 | 0.3033 | 200 | 0.0593 |
| 0.053 | 0.3791 | 250 | 0.0517 |
| 0.0489 | 0.4550 | 300 | 0.0463 |
| 0.0525 | 0.5308 | 350 | 0.0471 |
| 0.0651 | 0.6066 | 400 | 0.0472 |
| 0.0552 | 0.6825 | 450 | 0.0467 |
| 0.0317 | 0.7583 | 500 | 0.0416 |
| 0.0313 | 0.8341 | 550 | 0.0426 |
| 0.0441 | 0.9100 | 600 | 0.0429 |
| 0.0436 | 0.9858 | 650 | 0.0390 |
| 0.0324 | 1.0616 | 700 | 0.0417 |
| 0.0356 | 1.1374 | 750 | 0.0421 |
| 0.0368 | 1.2133 | 800 | 0.0378 |
| 0.0322 | 1.2891 | 850 | 0.0418 |
| 0.0242 | 1.3649 | 900 | 0.0404 |
| 0.0278 | 1.4408 | 950 | 0.0395 |
| 0.0391 | 1.5166 | 1000 | 0.0356 |
| 0.0294 | 1.5924 | 1050 | 0.0360 |
| 0.023 | 1.6682 | 1100 | 0.0359 |
| 0.0282 | 1.7441 | 1150 | 0.0372 |
| 0.0343 | 1.8199 | 1200 | 0.0359 |
| 0.0335 | 1.8957 | 1250 | 0.0339 |
| 0.0389 | 1.9716 | 1300 | 0.0357 |
| 0.0277 | 2.0474 | 1350 | 0.0351 |
| 0.0193 | 2.1232 | 1400 | 0.0343 |
| 0.0211 | 2.1991 | 1450 | 0.0354 |
| 0.0149 | 2.2749 | 1500 | 0.0352 |
| 0.0258 | 2.3507 | 1550 | 0.0337 |
| 0.0255 | 2.4265 | 1600 | 0.0359 |
| 0.014 | 2.5024 | 1650 | 0.0377 |
| 0.0265 | 2.5782 | 1700 | 0.0336 |
| 0.0211 | 2.6540 | 1750 | 0.0344 |
| 0.0278 | 2.7299 | 1800 | 0.0355 |
| 0.0253 | 2.8057 | 1850 | 0.0363 |
| 0.0178 | 2.8815 | 1900 | 0.0345 |
| 0.0302 | 2.9573 | 1950 | 0.0340 |
| 0.0091 | 3.0332 | 2000 | 0.0358 |
| 0.0072 | 3.1090 | 2050 | 0.0411 |
| 0.0126 | 3.1848 | 2100 | 0.0394 |
| 0.0108 | 3.2607 | 2150 | 0.0404 |
| 0.0101 | 3.3365 | 2200 | 0.0381 |
| 0.0077 | 3.4123 | 2250 | 0.0382 |
| 0.0096 | 3.4882 | 2300 | 0.0379 |
| 0.0077 | 3.5640 | 2350 | 0.0392 |
| 0.015 | 3.6398 | 2400 | 0.0381 |
| 0.0095 | 3.7156 | 2450 | 0.0401 |
| 0.0174 | 3.7915 | 2500 | 0.0395 |
| 0.0105 | 3.8673 | 2550 | 0.0393 |
| 0.014 | 3.9431 | 2600 | 0.0385 |
| 0.0086 | 4.0190 | 2650 | 0.0402 |
| 0.005 | 4.0948 | 2700 | 0.0439 |
| 0.0044 | 4.1706 | 2750 | 0.0487 |
| 0.0032 | 4.2464 | 2800 | 0.0490 |
| 0.0052 | 4.3223 | 2850 | 0.0489 |
| 0.0089 | 4.3981 | 2900 | 0.0493 |
| 0.0095 | 4.4739 | 2950 | 0.0490 |
| 0.0049 | 4.5498 | 3000 | 0.0487 |
| 0.0025 | 4.6256 | 3050 | 0.0492 |
| 0.0066 | 4.7014 | 3100 | 0.0498 |
| 0.0089 | 4.7773 | 3150 | 0.0500 |
| 0.0021 | 4.8531 | 3200 | 0.0500 |
| 0.0056 | 4.9289 | 3250 | 0.0499 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |