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---
library_name: peft
license: mit
base_model: klyang/MentaLLaMA-chat-7B-hf
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: MentaLLaMA-chat-7B-PsyCourse-fold1
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. -->
# MentaLLaMA-chat-7B-PsyCourse-fold1
This model is a fine-tuned version of [klyang/MentaLLaMA-chat-7B-hf](https://huggingface.co/klyang/MentaLLaMA-chat-7B-hf) on the course-train-fold1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0286
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7547 | 0.0770 | 50 | 0.6286 |
| 0.1561 | 0.1539 | 100 | 0.1107 |
| 0.0844 | 0.2309 | 150 | 0.0686 |
| 0.072 | 0.3078 | 200 | 0.0540 |
| 0.0458 | 0.3848 | 250 | 0.0526 |
| 0.0511 | 0.4617 | 300 | 0.0490 |
| 0.0479 | 0.5387 | 350 | 0.0436 |
| 0.0648 | 0.6156 | 400 | 0.0458 |
| 0.0355 | 0.6926 | 450 | 0.0410 |
| 0.0335 | 0.7695 | 500 | 0.0391 |
| 0.0478 | 0.8465 | 550 | 0.0351 |
| 0.0332 | 0.9234 | 600 | 0.0336 |
| 0.0275 | 1.0004 | 650 | 0.0333 |
| 0.0361 | 1.0773 | 700 | 0.0354 |
| 0.0303 | 1.1543 | 750 | 0.0327 |
| 0.0288 | 1.2312 | 800 | 0.0326 |
| 0.0316 | 1.3082 | 850 | 0.0336 |
| 0.0222 | 1.3851 | 900 | 0.0325 |
| 0.0373 | 1.4621 | 950 | 0.0345 |
| 0.0335 | 1.5391 | 1000 | 0.0325 |
| 0.0316 | 1.6160 | 1050 | 0.0308 |
| 0.0317 | 1.6930 | 1100 | 0.0317 |
| 0.0214 | 1.7699 | 1150 | 0.0310 |
| 0.0203 | 1.8469 | 1200 | 0.0319 |
| 0.027 | 1.9238 | 1250 | 0.0299 |
| 0.0202 | 2.0008 | 1300 | 0.0291 |
| 0.0184 | 2.0777 | 1350 | 0.0298 |
| 0.0297 | 2.1547 | 1400 | 0.0300 |
| 0.015 | 2.2316 | 1450 | 0.0330 |
| 0.0205 | 2.3086 | 1500 | 0.0309 |
| 0.0169 | 2.3855 | 1550 | 0.0316 |
| 0.0155 | 2.4625 | 1600 | 0.0323 |
| 0.0216 | 2.5394 | 1650 | 0.0298 |
| 0.016 | 2.6164 | 1700 | 0.0289 |
| 0.0255 | 2.6933 | 1750 | 0.0295 |
| 0.0212 | 2.7703 | 1800 | 0.0297 |
| 0.0236 | 2.8472 | 1850 | 0.0286 |
| 0.0184 | 2.9242 | 1900 | 0.0291 |
| 0.0255 | 3.0012 | 1950 | 0.0290 |
| 0.0122 | 3.0781 | 2000 | 0.0292 |
| 0.0108 | 3.1551 | 2050 | 0.0306 |
| 0.0087 | 3.2320 | 2100 | 0.0324 |
| 0.009 | 3.3090 | 2150 | 0.0330 |
| 0.0149 | 3.3859 | 2200 | 0.0317 |
| 0.0127 | 3.4629 | 2250 | 0.0319 |
| 0.0139 | 3.5398 | 2300 | 0.0329 |
| 0.008 | 3.6168 | 2350 | 0.0325 |
| 0.0118 | 3.6937 | 2400 | 0.0335 |
| 0.008 | 3.7707 | 2450 | 0.0331 |
| 0.0092 | 3.8476 | 2500 | 0.0335 |
| 0.01 | 3.9246 | 2550 | 0.0339 |
| 0.0128 | 4.0015 | 2600 | 0.0343 |
| 0.0028 | 4.0785 | 2650 | 0.0353 |
| 0.0072 | 4.1554 | 2700 | 0.0368 |
| 0.004 | 4.2324 | 2750 | 0.0372 |
| 0.004 | 4.3093 | 2800 | 0.0383 |
| 0.0042 | 4.3863 | 2850 | 0.0391 |
| 0.0047 | 4.4633 | 2900 | 0.0393 |
| 0.0029 | 4.5402 | 2950 | 0.0393 |
| 0.0043 | 4.6172 | 3000 | 0.0393 |
| 0.005 | 4.6941 | 3050 | 0.0392 |
| 0.0065 | 4.7711 | 3100 | 0.0393 |
| 0.01 | 4.8480 | 3150 | 0.0392 |
| 0.0031 | 4.9250 | 3200 | 0.0393 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |