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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-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. -->
# MentaLLaMA-chat-7B-PsyCourse-fold6
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-fold6 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0319
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8292 | 0.0751 | 50 | 0.6473 |
| 0.1595 | 0.1502 | 100 | 0.1169 |
| 0.0933 | 0.2254 | 150 | 0.0727 |
| 0.0512 | 0.3005 | 200 | 0.0581 |
| 0.0619 | 0.3756 | 250 | 0.0474 |
| 0.0395 | 0.4507 | 300 | 0.0460 |
| 0.0476 | 0.5258 | 350 | 0.0454 |
| 0.0444 | 0.6009 | 400 | 0.0407 |
| 0.0543 | 0.6761 | 450 | 0.0425 |
| 0.0454 | 0.7512 | 500 | 0.0372 |
| 0.0562 | 0.8263 | 550 | 0.0377 |
| 0.0336 | 0.9014 | 600 | 0.0361 |
| 0.0494 | 0.9765 | 650 | 0.0368 |
| 0.0354 | 1.0516 | 700 | 0.0386 |
| 0.029 | 1.1268 | 750 | 0.0376 |
| 0.0301 | 1.2019 | 800 | 0.0352 |
| 0.0321 | 1.2770 | 850 | 0.0341 |
| 0.0271 | 1.3521 | 900 | 0.0343 |
| 0.0351 | 1.4272 | 950 | 0.0330 |
| 0.0244 | 1.5023 | 1000 | 0.0330 |
| 0.0277 | 1.5775 | 1050 | 0.0341 |
| 0.0231 | 1.6526 | 1100 | 0.0340 |
| 0.0261 | 1.7277 | 1150 | 0.0327 |
| 0.0297 | 1.8028 | 1200 | 0.0348 |
| 0.027 | 1.8779 | 1250 | 0.0334 |
| 0.0417 | 1.9531 | 1300 | 0.0348 |
| 0.0173 | 2.0282 | 1350 | 0.0328 |
| 0.0207 | 2.1033 | 1400 | 0.0323 |
| 0.0223 | 2.1784 | 1450 | 0.0325 |
| 0.0107 | 2.2535 | 1500 | 0.0359 |
| 0.0182 | 2.3286 | 1550 | 0.0332 |
| 0.0187 | 2.4038 | 1600 | 0.0323 |
| 0.018 | 2.4789 | 1650 | 0.0327 |
| 0.0205 | 2.5540 | 1700 | 0.0350 |
| 0.0182 | 2.6291 | 1750 | 0.0323 |
| 0.0202 | 2.7042 | 1800 | 0.0325 |
| 0.0218 | 2.7793 | 1850 | 0.0323 |
| 0.0179 | 2.8545 | 1900 | 0.0319 |
| 0.0213 | 2.9296 | 1950 | 0.0330 |
| 0.0104 | 3.0047 | 2000 | 0.0328 |
| 0.0097 | 3.0798 | 2050 | 0.0359 |
| 0.0103 | 3.1549 | 2100 | 0.0363 |
| 0.0131 | 3.2300 | 2150 | 0.0359 |
| 0.0149 | 3.3052 | 2200 | 0.0362 |
| 0.0083 | 3.3803 | 2250 | 0.0365 |
| 0.0115 | 3.4554 | 2300 | 0.0359 |
| 0.0111 | 3.5305 | 2350 | 0.0387 |
| 0.0094 | 3.6056 | 2400 | 0.0376 |
| 0.0051 | 3.6808 | 2450 | 0.0376 |
| 0.0053 | 3.7559 | 2500 | 0.0375 |
| 0.0078 | 3.8310 | 2550 | 0.0377 |
| 0.0105 | 3.9061 | 2600 | 0.0372 |
| 0.0105 | 3.9812 | 2650 | 0.0371 |
| 0.0064 | 4.0563 | 2700 | 0.0382 |
| 0.0048 | 4.1315 | 2750 | 0.0398 |
| 0.0065 | 4.2066 | 2800 | 0.0407 |
| 0.0031 | 4.2817 | 2850 | 0.0417 |
| 0.0028 | 4.3568 | 2900 | 0.0420 |
| 0.0043 | 4.4319 | 2950 | 0.0421 |
| 0.0048 | 4.5070 | 3000 | 0.0424 |
| 0.0038 | 4.5822 | 3050 | 0.0428 |
| 0.0041 | 4.6573 | 3100 | 0.0430 |
| 0.0066 | 4.7324 | 3150 | 0.0431 |
| 0.003 | 4.8075 | 3200 | 0.0430 |
| 0.0031 | 4.8826 | 3250 | 0.0429 |
| 0.0046 | 4.9577 | 3300 | 0.0430 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |