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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-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. -->
# MentaLLaMA-chat-7B-PsyCourse-fold5
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-fold5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0295
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8836 | 0.0758 | 50 | 0.6510 |
| 0.1276 | 0.1517 | 100 | 0.1150 |
| 0.0848 | 0.2275 | 150 | 0.0731 |
| 0.0545 | 0.3033 | 200 | 0.0569 |
| 0.0542 | 0.3791 | 250 | 0.0499 |
| 0.0466 | 0.4550 | 300 | 0.0510 |
| 0.0517 | 0.5308 | 350 | 0.0468 |
| 0.058 | 0.6066 | 400 | 0.0456 |
| 0.0521 | 0.6825 | 450 | 0.0405 |
| 0.0317 | 0.7583 | 500 | 0.0382 |
| 0.0281 | 0.8341 | 550 | 0.0390 |
| 0.0388 | 0.9100 | 600 | 0.0388 |
| 0.0459 | 0.9858 | 650 | 0.0355 |
| 0.0277 | 1.0616 | 700 | 0.0368 |
| 0.0342 | 1.1374 | 750 | 0.0369 |
| 0.0323 | 1.2133 | 800 | 0.0337 |
| 0.0257 | 1.2891 | 850 | 0.0351 |
| 0.0218 | 1.3649 | 900 | 0.0346 |
| 0.0266 | 1.4408 | 950 | 0.0377 |
| 0.0344 | 1.5166 | 1000 | 0.0322 |
| 0.0244 | 1.5924 | 1050 | 0.0315 |
| 0.0227 | 1.6682 | 1100 | 0.0332 |
| 0.0243 | 1.7441 | 1150 | 0.0318 |
| 0.03 | 1.8199 | 1200 | 0.0311 |
| 0.0307 | 1.8957 | 1250 | 0.0295 |
| 0.0344 | 1.9716 | 1300 | 0.0305 |
| 0.0214 | 2.0474 | 1350 | 0.0307 |
| 0.0178 | 2.1232 | 1400 | 0.0320 |
| 0.0167 | 2.1991 | 1450 | 0.0321 |
| 0.0115 | 2.2749 | 1500 | 0.0325 |
| 0.0192 | 2.3507 | 1550 | 0.0318 |
| 0.0233 | 2.4265 | 1600 | 0.0327 |
| 0.0108 | 2.5024 | 1650 | 0.0340 |
| 0.0256 | 2.5782 | 1700 | 0.0315 |
| 0.019 | 2.6540 | 1750 | 0.0300 |
| 0.0205 | 2.7299 | 1800 | 0.0302 |
| 0.0197 | 2.8057 | 1850 | 0.0307 |
| 0.0161 | 2.8815 | 1900 | 0.0303 |
| 0.0235 | 2.9573 | 1950 | 0.0302 |
| 0.01 | 3.0332 | 2000 | 0.0301 |
| 0.0073 | 3.1090 | 2050 | 0.0325 |
| 0.0099 | 3.1848 | 2100 | 0.0337 |
| 0.0085 | 3.2607 | 2150 | 0.0337 |
| 0.0076 | 3.3365 | 2200 | 0.0354 |
| 0.0077 | 3.4123 | 2250 | 0.0341 |
| 0.0107 | 3.4882 | 2300 | 0.0338 |
| 0.006 | 3.5640 | 2350 | 0.0338 |
| 0.0127 | 3.6398 | 2400 | 0.0336 |
| 0.0099 | 3.7156 | 2450 | 0.0338 |
| 0.014 | 3.7915 | 2500 | 0.0337 |
| 0.0129 | 3.8673 | 2550 | 0.0339 |
| 0.0118 | 3.9431 | 2600 | 0.0350 |
| 0.0073 | 4.0190 | 2650 | 0.0346 |
| 0.0048 | 4.0948 | 2700 | 0.0357 |
| 0.0059 | 4.1706 | 2750 | 0.0373 |
| 0.0053 | 4.2464 | 2800 | 0.0373 |
| 0.0045 | 4.3223 | 2850 | 0.0381 |
| 0.0054 | 4.3981 | 2900 | 0.0388 |
| 0.0085 | 4.4739 | 2950 | 0.0385 |
| 0.0066 | 4.5498 | 3000 | 0.0384 |
| 0.0051 | 4.6256 | 3050 | 0.0386 |
| 0.0052 | 4.7014 | 3100 | 0.0388 |
| 0.0065 | 4.7773 | 3150 | 0.0389 |
| 0.0036 | 4.8531 | 3200 | 0.0391 |
| 0.0039 | 4.9289 | 3250 | 0.0391 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |