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Qwen2.5-7B-Instruct-PsyCourse-fold8

PEFT
Safetensors
llama-factory
lora
Generated from Trainer
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1
- ---
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- library_name: peft
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- license: apache-2.0
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- base_model: Qwen/Qwen2.5-7B-Instruct
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- tags:
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- - llama-factory
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- - lora
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- - generated_from_trainer
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- model-index:
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- - name: Qwen2.5-7B-Instruct-PsyCourse-fold8
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- results: []
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- ---
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-
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- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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-
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- # Qwen2.5-7B-Instruct-PsyCourse-fold8
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-
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- This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the course-train-fold1 dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.0314
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-
23
- ## Model description
24
-
25
- More information needed
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-
27
- ## Intended uses & limitations
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-
29
- More information needed
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-
31
- ## Training and evaluation data
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-
33
- More information needed
34
-
35
- ## Training procedure
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-
37
- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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- - train_batch_size: 1
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- - eval_batch_size: 1
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- - seed: 42
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- - gradient_accumulation_steps: 16
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- - total_train_batch_size: 16
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- - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- - lr_scheduler_type: cosine
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- - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 5.0
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:------:|:----:|:---------------:|
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- | 0.8741 | 0.0770 | 50 | 0.6942 |
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- | 0.1568 | 0.1539 | 100 | 0.1080 |
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- | 0.0871 | 0.2309 | 150 | 0.0727 |
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- | 0.0731 | 0.3078 | 200 | 0.0559 |
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- | 0.0543 | 0.3848 | 250 | 0.0530 |
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- | 0.0527 | 0.4617 | 300 | 0.0502 |
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- | 0.0465 | 0.5387 | 350 | 0.0473 |
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- | 0.0624 | 0.6156 | 400 | 0.0441 |
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- | 0.0356 | 0.6926 | 450 | 0.0440 |
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- | 0.0298 | 0.7695 | 500 | 0.0410 |
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- | 0.0477 | 0.8465 | 550 | 0.0382 |
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- | 0.0369 | 0.9234 | 600 | 0.0370 |
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- | 0.0295 | 1.0004 | 650 | 0.0362 |
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- | 0.0366 | 1.0773 | 700 | 0.0367 |
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- | 0.0303 | 1.1543 | 750 | 0.0354 |
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- | 0.031 | 1.2312 | 800 | 0.0347 |
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- | 0.0345 | 1.3082 | 850 | 0.0350 |
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- | 0.0203 | 1.3851 | 900 | 0.0337 |
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- | 0.0406 | 1.4621 | 950 | 0.0343 |
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- | 0.0326 | 1.5391 | 1000 | 0.0331 |
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- | 0.0325 | 1.6160 | 1050 | 0.0332 |
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- | 0.0328 | 1.6930 | 1100 | 0.0352 |
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- | 0.0198 | 1.7699 | 1150 | 0.0329 |
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- | 0.0202 | 1.8469 | 1200 | 0.0345 |
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- | 0.0301 | 1.9238 | 1250 | 0.0337 |
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- | 0.022 | 2.0008 | 1300 | 0.0315 |
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- | 0.0159 | 2.0777 | 1350 | 0.0325 |
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- | 0.0304 | 2.1547 | 1400 | 0.0349 |
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- | 0.0145 | 2.2316 | 1450 | 0.0354 |
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- | 0.0191 | 2.3086 | 1500 | 0.0334 |
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- | 0.015 | 2.3855 | 1550 | 0.0350 |
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- | 0.0151 | 2.4625 | 1600 | 0.0343 |
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- | 0.022 | 2.5394 | 1650 | 0.0330 |
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- | 0.0192 | 2.6164 | 1700 | 0.0328 |
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- | 0.0266 | 2.6933 | 1750 | 0.0314 |
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- | 0.0246 | 2.7703 | 1800 | 0.0329 |
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- | 0.022 | 2.8472 | 1850 | 0.0318 |
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- | 0.0172 | 2.9242 | 1900 | 0.0331 |
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- | 0.0294 | 3.0012 | 1950 | 0.0331 |
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- | 0.0117 | 3.0781 | 2000 | 0.0357 |
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- | 0.0092 | 3.1551 | 2050 | 0.0390 |
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- | 0.0077 | 3.2320 | 2100 | 0.0402 |
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- | 0.012 | 3.3090 | 2150 | 0.0381 |
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- | 0.0122 | 3.3859 | 2200 | 0.0389 |
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- | 0.0099 | 3.4629 | 2250 | 0.0390 |
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- | 0.0105 | 3.5398 | 2300 | 0.0394 |
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- | 0.0063 | 3.6168 | 2350 | 0.0401 |
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- | 0.0125 | 3.6937 | 2400 | 0.0391 |
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- | 0.0072 | 3.7707 | 2450 | 0.0401 |
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- | 0.008 | 3.8476 | 2500 | 0.0405 |
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- | 0.0134 | 3.9246 | 2550 | 0.0413 |
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- | 0.0106 | 4.0015 | 2600 | 0.0411 |
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- | 0.0019 | 4.0785 | 2650 | 0.0424 |
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- | 0.0046 | 4.1554 | 2700 | 0.0454 |
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- | 0.0024 | 4.2324 | 2750 | 0.0470 |
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- | 0.0043 | 4.3093 | 2800 | 0.0478 |
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- | 0.0035 | 4.3863 | 2850 | 0.0488 |
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- | 0.0043 | 4.4633 | 2900 | 0.0488 |
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- | 0.0019 | 4.5402 | 2950 | 0.0487 |
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- | 0.0026 | 4.6172 | 3000 | 0.0490 |
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- | 0.0043 | 4.6941 | 3050 | 0.0491 |
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- | 0.0028 | 4.7711 | 3100 | 0.0494 |
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- | 0.0056 | 4.8480 | 3150 | 0.0493 |
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- | 0.002 | 4.9250 | 3200 | 0.0492 |
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-
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-
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- ### Framework versions
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-
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- - PEFT 0.12.0
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- - Transformers 4.46.1
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- - Pytorch 2.5.1+cu124
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- - Datasets 3.1.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - Tokenizers 0.20.3
 
1
+ ---
2
+ library_name: peft
3
+ license: apache-2.0
4
+ base_model: Qwen/Qwen2.5-7B-Instruct
5
+ tags:
6
+ - llama-factory
7
+ - lora
8
+ - generated_from_trainer
9
+ language:
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+ - zho
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+ - eng
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+ - fra
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+ - spa
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+ - por
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+ - deu
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+ - ita
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+ - rus
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+ - jpn
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+ - kor
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+ - vie
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+ - tha
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+ - ara
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+ model-index:
24
+ - name: Qwen2.5-7B-Instruct-PsyCourse-fold8
25
+ results: []
26
+ ---
27
+
28
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
29
+ should probably proofread and complete it, then remove this comment. -->
30
+
31
+ # Qwen2.5-7B-Instruct-PsyCourse-fold8
32
+
33
+ This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the course-train-fold1 dataset.
34
+ It achieves the following results on the evaluation set:
35
+ - Loss: 0.0314
36
+
37
+ ## Model description
38
+
39
+ More information needed
40
+
41
+ ## Intended uses & limitations
42
+
43
+ More information needed
44
+
45
+ ## Training and evaluation data
46
+
47
+ More information needed
48
+
49
+ ## Training procedure
50
+
51
+ ### Training hyperparameters
52
+
53
+ The following hyperparameters were used during training:
54
+ - learning_rate: 0.0001
55
+ - train_batch_size: 1
56
+ - eval_batch_size: 1
57
+ - seed: 42
58
+ - gradient_accumulation_steps: 16
59
+ - total_train_batch_size: 16
60
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
61
+ - lr_scheduler_type: cosine
62
+ - lr_scheduler_warmup_ratio: 0.1
63
+ - num_epochs: 5.0
64
+
65
+ ### Training results
66
+
67
+ | Training Loss | Epoch | Step | Validation Loss |
68
+ |:-------------:|:------:|:----:|:---------------:|
69
+ | 0.8741 | 0.0770 | 50 | 0.6942 |
70
+ | 0.1568 | 0.1539 | 100 | 0.1080 |
71
+ | 0.0871 | 0.2309 | 150 | 0.0727 |
72
+ | 0.0731 | 0.3078 | 200 | 0.0559 |
73
+ | 0.0543 | 0.3848 | 250 | 0.0530 |
74
+ | 0.0527 | 0.4617 | 300 | 0.0502 |
75
+ | 0.0465 | 0.5387 | 350 | 0.0473 |
76
+ | 0.0624 | 0.6156 | 400 | 0.0441 |
77
+ | 0.0356 | 0.6926 | 450 | 0.0440 |
78
+ | 0.0298 | 0.7695 | 500 | 0.0410 |
79
+ | 0.0477 | 0.8465 | 550 | 0.0382 |
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+ | 0.0369 | 0.9234 | 600 | 0.0370 |
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+ | 0.0295 | 1.0004 | 650 | 0.0362 |
82
+ | 0.0366 | 1.0773 | 700 | 0.0367 |
83
+ | 0.0303 | 1.1543 | 750 | 0.0354 |
84
+ | 0.031 | 1.2312 | 800 | 0.0347 |
85
+ | 0.0345 | 1.3082 | 850 | 0.0350 |
86
+ | 0.0203 | 1.3851 | 900 | 0.0337 |
87
+ | 0.0406 | 1.4621 | 950 | 0.0343 |
88
+ | 0.0326 | 1.5391 | 1000 | 0.0331 |
89
+ | 0.0325 | 1.6160 | 1050 | 0.0332 |
90
+ | 0.0328 | 1.6930 | 1100 | 0.0352 |
91
+ | 0.0198 | 1.7699 | 1150 | 0.0329 |
92
+ | 0.0202 | 1.8469 | 1200 | 0.0345 |
93
+ | 0.0301 | 1.9238 | 1250 | 0.0337 |
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+ | 0.022 | 2.0008 | 1300 | 0.0315 |
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+ | 0.0159 | 2.0777 | 1350 | 0.0325 |
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+ | 0.0304 | 2.1547 | 1400 | 0.0349 |
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+ | 0.0145 | 2.2316 | 1450 | 0.0354 |
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+ | 0.0191 | 2.3086 | 1500 | 0.0334 |
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+ | 0.015 | 2.3855 | 1550 | 0.0350 |
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+ | 0.0151 | 2.4625 | 1600 | 0.0343 |
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+ | 0.022 | 2.5394 | 1650 | 0.0330 |
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+ | 0.0192 | 2.6164 | 1700 | 0.0328 |
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+ | 0.0266 | 2.6933 | 1750 | 0.0314 |
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+ | 0.0246 | 2.7703 | 1800 | 0.0329 |
105
+ | 0.022 | 2.8472 | 1850 | 0.0318 |
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+ | 0.0172 | 2.9242 | 1900 | 0.0331 |
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+ | 0.0294 | 3.0012 | 1950 | 0.0331 |
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+ | 0.0117 | 3.0781 | 2000 | 0.0357 |
109
+ | 0.0092 | 3.1551 | 2050 | 0.0390 |
110
+ | 0.0077 | 3.2320 | 2100 | 0.0402 |
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+ | 0.012 | 3.3090 | 2150 | 0.0381 |
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+ | 0.0122 | 3.3859 | 2200 | 0.0389 |
113
+ | 0.0099 | 3.4629 | 2250 | 0.0390 |
114
+ | 0.0105 | 3.5398 | 2300 | 0.0394 |
115
+ | 0.0063 | 3.6168 | 2350 | 0.0401 |
116
+ | 0.0125 | 3.6937 | 2400 | 0.0391 |
117
+ | 0.0072 | 3.7707 | 2450 | 0.0401 |
118
+ | 0.008 | 3.8476 | 2500 | 0.0405 |
119
+ | 0.0134 | 3.9246 | 2550 | 0.0413 |
120
+ | 0.0106 | 4.0015 | 2600 | 0.0411 |
121
+ | 0.0019 | 4.0785 | 2650 | 0.0424 |
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+ | 0.0046 | 4.1554 | 2700 | 0.0454 |
123
+ | 0.0024 | 4.2324 | 2750 | 0.0470 |
124
+ | 0.0043 | 4.3093 | 2800 | 0.0478 |
125
+ | 0.0035 | 4.3863 | 2850 | 0.0488 |
126
+ | 0.0043 | 4.4633 | 2900 | 0.0488 |
127
+ | 0.0019 | 4.5402 | 2950 | 0.0487 |
128
+ | 0.0026 | 4.6172 | 3000 | 0.0490 |
129
+ | 0.0043 | 4.6941 | 3050 | 0.0491 |
130
+ | 0.0028 | 4.7711 | 3100 | 0.0494 |
131
+ | 0.0056 | 4.8480 | 3150 | 0.0493 |
132
+ | 0.002 | 4.9250 | 3200 | 0.0492 |
133
+
134
+
135
+ ### Framework versions
136
+
137
+ - PEFT 0.12.0
138
+ - Transformers 4.46.1
139
+ - Pytorch 2.5.1+cu124
140
+ - Datasets 3.1.0
141
  - Tokenizers 0.20.3