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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-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. -->
# Llama-3.1-8B-Instruct-PsyCourse-fold4
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-fold4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0344
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.5681 | 0.0763 | 50 | 0.3814 |
| 0.122 | 0.1527 | 100 | 0.0796 |
| 0.0541 | 0.2290 | 150 | 0.0592 |
| 0.0502 | 0.3053 | 200 | 0.0522 |
| 0.0666 | 0.3816 | 250 | 0.0539 |
| 0.046 | 0.4580 | 300 | 0.0493 |
| 0.0458 | 0.5343 | 350 | 0.0527 |
| 0.0448 | 0.6106 | 400 | 0.0488 |
| 0.0567 | 0.6870 | 450 | 0.0462 |
| 0.0358 | 0.7633 | 500 | 0.0410 |
| 0.0445 | 0.8396 | 550 | 0.0407 |
| 0.0462 | 0.9159 | 600 | 0.0407 |
| 0.0363 | 0.9923 | 650 | 0.0410 |
| 0.0343 | 1.0686 | 700 | 0.0370 |
| 0.0413 | 1.1449 | 750 | 0.0378 |
| 0.0322 | 1.2213 | 800 | 0.0398 |
| 0.0342 | 1.2976 | 850 | 0.0385 |
| 0.0337 | 1.3739 | 900 | 0.0436 |
| 0.0295 | 1.4502 | 950 | 0.0373 |
| 0.0267 | 1.5266 | 1000 | 0.0386 |
| 0.0287 | 1.6029 | 1050 | 0.0380 |
| 0.0504 | 1.6792 | 1100 | 0.0388 |
| 0.0317 | 1.7556 | 1150 | 0.0391 |
| 0.0448 | 1.8319 | 1200 | 0.0366 |
| 0.0278 | 1.9082 | 1250 | 0.0362 |
| 0.0347 | 1.9845 | 1300 | 0.0344 |
| 0.0201 | 2.0609 | 1350 | 0.0355 |
| 0.0238 | 2.1372 | 1400 | 0.0357 |
| 0.0299 | 2.2135 | 1450 | 0.0371 |
| 0.0155 | 2.2899 | 1500 | 0.0384 |
| 0.0157 | 2.3662 | 1550 | 0.0391 |
| 0.0222 | 2.4425 | 1600 | 0.0370 |
| 0.0245 | 2.5188 | 1650 | 0.0360 |
| 0.0206 | 2.5952 | 1700 | 0.0376 |
| 0.0198 | 2.6715 | 1750 | 0.0363 |
| 0.0209 | 2.7478 | 1800 | 0.0370 |
| 0.026 | 2.8242 | 1850 | 0.0362 |
| 0.0197 | 2.9005 | 1900 | 0.0358 |
| 0.0291 | 2.9768 | 1950 | 0.0355 |
| 0.0091 | 3.0531 | 2000 | 0.0416 |
| 0.0132 | 3.1295 | 2050 | 0.0421 |
| 0.0115 | 3.2058 | 2100 | 0.0443 |
| 0.0131 | 3.2821 | 2150 | 0.0459 |
| 0.0132 | 3.3585 | 2200 | 0.0409 |
| 0.0077 | 3.4348 | 2250 | 0.0445 |
| 0.0156 | 3.5111 | 2300 | 0.0444 |
| 0.0125 | 3.5874 | 2350 | 0.0480 |
| 0.0089 | 3.6638 | 2400 | 0.0499 |
| 0.0125 | 3.7401 | 2450 | 0.0467 |
| 0.0115 | 3.8164 | 2500 | 0.0447 |
| 0.0062 | 3.8928 | 2550 | 0.0449 |
| 0.0112 | 3.9691 | 2600 | 0.0462 |
| 0.005 | 4.0454 | 2650 | 0.0465 |
| 0.0065 | 4.1217 | 2700 | 0.0502 |
| 0.0021 | 4.1981 | 2750 | 0.0543 |
| 0.0033 | 4.2744 | 2800 | 0.0556 |
| 0.0068 | 4.3507 | 2850 | 0.0572 |
| 0.0015 | 4.4271 | 2900 | 0.0599 |
| 0.0036 | 4.5034 | 2950 | 0.0602 |
| 0.0027 | 4.5797 | 3000 | 0.0615 |
| 0.0013 | 4.6560 | 3050 | 0.0615 |
| 0.0056 | 4.7324 | 3100 | 0.0618 |
| 0.0028 | 4.8087 | 3150 | 0.0618 |
| 0.0044 | 4.8850 | 3200 | 0.0620 |
| 0.0061 | 4.9614 | 3250 | 0.0622 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |