File size: 4,979 Bytes
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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-fold6
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-fold6
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-fold6 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0368
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.6045 | 0.0751 | 50 | 0.4191 |
| 0.118 | 0.1502 | 100 | 0.0976 |
| 0.075 | 0.2254 | 150 | 0.0908 |
| 0.0475 | 0.3005 | 200 | 0.0555 |
| 0.0612 | 0.3756 | 250 | 0.0530 |
| 0.043 | 0.4507 | 300 | 0.0526 |
| 0.0497 | 0.5258 | 350 | 0.0503 |
| 0.049 | 0.6009 | 400 | 0.0481 |
| 0.0541 | 0.6761 | 450 | 0.0477 |
| 0.0494 | 0.7512 | 500 | 0.0432 |
| 0.0556 | 0.8263 | 550 | 0.0414 |
| 0.0398 | 0.9014 | 600 | 0.0415 |
| 0.0535 | 0.9765 | 650 | 0.0429 |
| 0.0383 | 1.0516 | 700 | 0.0438 |
| 0.0317 | 1.1268 | 750 | 0.0409 |
| 0.0311 | 1.2019 | 800 | 0.0410 |
| 0.0351 | 1.2770 | 850 | 0.0398 |
| 0.0309 | 1.3521 | 900 | 0.0372 |
| 0.0373 | 1.4272 | 950 | 0.0383 |
| 0.0295 | 1.5023 | 1000 | 0.0397 |
| 0.0349 | 1.5775 | 1050 | 0.0408 |
| 0.026 | 1.6526 | 1100 | 0.0410 |
| 0.0305 | 1.7277 | 1150 | 0.0390 |
| 0.0332 | 1.8028 | 1200 | 0.0385 |
| 0.0304 | 1.8779 | 1250 | 0.0379 |
| 0.0497 | 1.9531 | 1300 | 0.0392 |
| 0.0183 | 2.0282 | 1350 | 0.0412 |
| 0.0269 | 2.1033 | 1400 | 0.0381 |
| 0.0299 | 2.1784 | 1450 | 0.0379 |
| 0.0129 | 2.2535 | 1500 | 0.0434 |
| 0.0203 | 2.3286 | 1550 | 0.0383 |
| 0.0221 | 2.4038 | 1600 | 0.0397 |
| 0.023 | 2.4789 | 1650 | 0.0413 |
| 0.0257 | 2.5540 | 1700 | 0.0409 |
| 0.0241 | 2.6291 | 1750 | 0.0400 |
| 0.0258 | 2.7042 | 1800 | 0.0405 |
| 0.021 | 2.7793 | 1850 | 0.0392 |
| 0.0253 | 2.8545 | 1900 | 0.0368 |
| 0.018 | 2.9296 | 1950 | 0.0392 |
| 0.0112 | 3.0047 | 2000 | 0.0407 |
| 0.0082 | 3.0798 | 2050 | 0.0478 |
| 0.0127 | 3.1549 | 2100 | 0.0460 |
| 0.0112 | 3.2300 | 2150 | 0.0449 |
| 0.0145 | 3.3052 | 2200 | 0.0452 |
| 0.0086 | 3.3803 | 2250 | 0.0451 |
| 0.0161 | 3.4554 | 2300 | 0.0490 |
| 0.0134 | 3.5305 | 2350 | 0.0465 |
| 0.009 | 3.6056 | 2400 | 0.0461 |
| 0.0056 | 3.6808 | 2450 | 0.0480 |
| 0.0069 | 3.7559 | 2500 | 0.0490 |
| 0.007 | 3.8310 | 2550 | 0.0489 |
| 0.0147 | 3.9061 | 2600 | 0.0480 |
| 0.0123 | 3.9812 | 2650 | 0.0474 |
| 0.0053 | 4.0563 | 2700 | 0.0529 |
| 0.0064 | 4.1315 | 2750 | 0.0571 |
| 0.0064 | 4.2066 | 2800 | 0.0590 |
| 0.0038 | 4.2817 | 2850 | 0.0607 |
| 0.0011 | 4.3568 | 2900 | 0.0627 |
| 0.0034 | 4.4319 | 2950 | 0.0627 |
| 0.0063 | 4.5070 | 3000 | 0.0623 |
| 0.0033 | 4.5822 | 3050 | 0.0635 |
| 0.0048 | 4.6573 | 3100 | 0.0643 |
| 0.0044 | 4.7324 | 3150 | 0.0636 |
| 0.0031 | 4.8075 | 3200 | 0.0636 |
| 0.0022 | 4.8826 | 3250 | 0.0639 |
| 0.0078 | 4.9577 | 3300 | 0.0638 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |