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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-fold7
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-fold7
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-fold7 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0272
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8412 | 0.0764 | 50 | 0.6190 |
| 0.1455 | 0.1528 | 100 | 0.1069 |
| 0.0861 | 0.2292 | 150 | 0.0647 |
| 0.0575 | 0.3056 | 200 | 0.0518 |
| 0.0643 | 0.3820 | 250 | 0.0469 |
| 0.0341 | 0.4584 | 300 | 0.0435 |
| 0.0641 | 0.5348 | 350 | 0.0413 |
| 0.0405 | 0.6112 | 400 | 0.0419 |
| 0.0531 | 0.6875 | 450 | 0.0385 |
| 0.041 | 0.7639 | 500 | 0.0372 |
| 0.0283 | 0.8403 | 550 | 0.0353 |
| 0.041 | 0.9167 | 600 | 0.0330 |
| 0.0553 | 0.9931 | 650 | 0.0363 |
| 0.0314 | 1.0695 | 700 | 0.0310 |
| 0.0211 | 1.1459 | 750 | 0.0312 |
| 0.0314 | 1.2223 | 800 | 0.0320 |
| 0.0325 | 1.2987 | 850 | 0.0315 |
| 0.0351 | 1.3751 | 900 | 0.0305 |
| 0.0402 | 1.4515 | 950 | 0.0314 |
| 0.0262 | 1.5279 | 1000 | 0.0299 |
| 0.026 | 1.6043 | 1050 | 0.0302 |
| 0.024 | 1.6807 | 1100 | 0.0314 |
| 0.0487 | 1.7571 | 1150 | 0.0302 |
| 0.0251 | 1.8335 | 1200 | 0.0300 |
| 0.028 | 1.9099 | 1250 | 0.0320 |
| 0.0244 | 1.9862 | 1300 | 0.0299 |
| 0.0211 | 2.0626 | 1350 | 0.0282 |
| 0.019 | 2.1390 | 1400 | 0.0285 |
| 0.012 | 2.2154 | 1450 | 0.0302 |
| 0.0181 | 2.2918 | 1500 | 0.0283 |
| 0.0176 | 2.3682 | 1550 | 0.0288 |
| 0.0136 | 2.4446 | 1600 | 0.0277 |
| 0.0217 | 2.5210 | 1650 | 0.0286 |
| 0.0156 | 2.5974 | 1700 | 0.0294 |
| 0.0191 | 2.6738 | 1750 | 0.0286 |
| 0.0249 | 2.7502 | 1800 | 0.0272 |
| 0.0237 | 2.8266 | 1850 | 0.0290 |
| 0.021 | 2.9030 | 1900 | 0.0278 |
| 0.0174 | 2.9794 | 1950 | 0.0283 |
| 0.0122 | 3.0558 | 2000 | 0.0290 |
| 0.0137 | 3.1322 | 2050 | 0.0301 |
| 0.0086 | 3.2086 | 2100 | 0.0309 |
| 0.0136 | 3.2850 | 2150 | 0.0306 |
| 0.0111 | 3.3613 | 2200 | 0.0310 |
| 0.0142 | 3.4377 | 2250 | 0.0327 |
| 0.0114 | 3.5141 | 2300 | 0.0312 |
| 0.015 | 3.5905 | 2350 | 0.0319 |
| 0.0088 | 3.6669 | 2400 | 0.0300 |
| 0.0068 | 3.7433 | 2450 | 0.0310 |
| 0.0098 | 3.8197 | 2500 | 0.0300 |
| 0.0088 | 3.8961 | 2550 | 0.0298 |
| 0.0081 | 3.9725 | 2600 | 0.0306 |
| 0.0052 | 4.0489 | 2650 | 0.0314 |
| 0.0076 | 4.1253 | 2700 | 0.0326 |
| 0.0091 | 4.2017 | 2750 | 0.0331 |
| 0.0045 | 4.2781 | 2800 | 0.0342 |
| 0.0047 | 4.3545 | 2850 | 0.0347 |
| 0.0047 | 4.4309 | 2900 | 0.0358 |
| 0.005 | 4.5073 | 2950 | 0.0359 |
| 0.0049 | 4.5837 | 3000 | 0.0363 |
| 0.0039 | 4.6600 | 3050 | 0.0363 |
| 0.0062 | 4.7364 | 3100 | 0.0366 |
| 0.0054 | 4.8128 | 3150 | 0.0366 |
| 0.0041 | 4.8892 | 3200 | 0.0366 |
| 0.0047 | 4.9656 | 3250 | 0.0366 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |