File size: 4,904 Bytes
fa3b0cc e8a97bf fa3b0cc e8a97bf fa3b0cc e8a97bf fa3b0cc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
---
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-fold9
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-fold9
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-fold9 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0305
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8389 | 0.0768 | 50 | 0.6107 |
| 0.1391 | 0.1535 | 100 | 0.1064 |
| 0.0757 | 0.2303 | 150 | 0.0694 |
| 0.0639 | 0.3070 | 200 | 0.0581 |
| 0.0739 | 0.3838 | 250 | 0.0467 |
| 0.0558 | 0.4606 | 300 | 0.0439 |
| 0.0394 | 0.5373 | 350 | 0.0425 |
| 0.0477 | 0.6141 | 400 | 0.0419 |
| 0.047 | 0.6908 | 450 | 0.0432 |
| 0.0416 | 0.7676 | 500 | 0.0376 |
| 0.0637 | 0.8444 | 550 | 0.0395 |
| 0.0377 | 0.9211 | 600 | 0.0357 |
| 0.0315 | 0.9979 | 650 | 0.0361 |
| 0.0332 | 1.0746 | 700 | 0.0360 |
| 0.0322 | 1.1514 | 750 | 0.0352 |
| 0.0321 | 1.2282 | 800 | 0.0333 |
| 0.0299 | 1.3049 | 850 | 0.0323 |
| 0.0286 | 1.3817 | 900 | 0.0340 |
| 0.0266 | 1.4585 | 950 | 0.0332 |
| 0.0296 | 1.5352 | 1000 | 0.0320 |
| 0.022 | 1.6120 | 1050 | 0.0307 |
| 0.0292 | 1.6887 | 1100 | 0.0312 |
| 0.0269 | 1.7655 | 1150 | 0.0330 |
| 0.0204 | 1.8423 | 1200 | 0.0306 |
| 0.0306 | 1.9190 | 1250 | 0.0309 |
| 0.0364 | 1.9958 | 1300 | 0.0314 |
| 0.0194 | 2.0725 | 1350 | 0.0319 |
| 0.0148 | 2.1493 | 1400 | 0.0318 |
| 0.0161 | 2.2261 | 1450 | 0.0305 |
| 0.0293 | 2.3028 | 1500 | 0.0323 |
| 0.0203 | 2.3796 | 1550 | 0.0329 |
| 0.0235 | 2.4563 | 1600 | 0.0327 |
| 0.0234 | 2.5331 | 1650 | 0.0311 |
| 0.0227 | 2.6099 | 1700 | 0.0307 |
| 0.0147 | 2.6866 | 1750 | 0.0313 |
| 0.0202 | 2.7634 | 1800 | 0.0322 |
| 0.0203 | 2.8401 | 1850 | 0.0313 |
| 0.0199 | 2.9169 | 1900 | 0.0310 |
| 0.0152 | 2.9937 | 1950 | 0.0315 |
| 0.0065 | 3.0704 | 2000 | 0.0347 |
| 0.0155 | 3.1472 | 2050 | 0.0345 |
| 0.0087 | 3.2239 | 2100 | 0.0367 |
| 0.0107 | 3.3007 | 2150 | 0.0353 |
| 0.0113 | 3.3775 | 2200 | 0.0377 |
| 0.0115 | 3.4542 | 2250 | 0.0358 |
| 0.0087 | 3.5310 | 2300 | 0.0377 |
| 0.0099 | 3.6078 | 2350 | 0.0374 |
| 0.0075 | 3.6845 | 2400 | 0.0381 |
| 0.0064 | 3.7613 | 2450 | 0.0384 |
| 0.0111 | 3.8380 | 2500 | 0.0382 |
| 0.0154 | 3.9148 | 2550 | 0.0380 |
| 0.0087 | 3.9916 | 2600 | 0.0379 |
| 0.0042 | 4.0683 | 2650 | 0.0392 |
| 0.0029 | 4.1451 | 2700 | 0.0411 |
| 0.0044 | 4.2218 | 2750 | 0.0422 |
| 0.0035 | 4.2986 | 2800 | 0.0430 |
| 0.0031 | 4.3754 | 2850 | 0.0441 |
| 0.004 | 4.4521 | 2900 | 0.0445 |
| 0.0035 | 4.5289 | 2950 | 0.0446 |
| 0.0021 | 4.6056 | 3000 | 0.0454 |
| 0.0041 | 4.6824 | 3050 | 0.0459 |
| 0.006 | 4.7592 | 3100 | 0.0456 |
| 0.0043 | 4.8359 | 3150 | 0.0455 |
| 0.0031 | 4.9127 | 3200 | 0.0456 |
| 0.0073 | 4.9894 | 3250 | 0.0456 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |