Hugging Face's logo

mtzig
/
v3_mistral_lora

PEFT
Safetensors
Generated from Trainer
Model card Files
xet
 Community
mtzig commited on
Commit
259c0ff
·
verified ·
1 Parent(s): 50d3933

Model save

Browse files
Files changed (3) hide show
  1. README.md +132 -0
  2. adapter_config.json +29 -0
  3. adapter_model.safetensors +3 -0
README.md ADDED
@@ -0,0 +1,132 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: peiyi9979/math-shepherd-mistral-7b-prm
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ - precision
9
+ - recall
10
+ - f1
11
+ model-index:
12
+ - name: v3_mistral_lora
13
+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
+ should probably proofread and complete it, then remove this comment. -->
18
+
19
+ # v3_mistral_lora
20
+
21
+ This model is a fine-tuned version of [peiyi9979/math-shepherd-mistral-7b-prm](https://huggingface.co/peiyi9979/math-shepherd-mistral-7b-prm) on an unknown dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: 0.0001
24
+ - Accuracy: 1.0
25
+ - Precision: 1.0
26
+ - Recall: 1.0
27
+ - F1: 1.0
28
+
29
+ ## Model description
30
+
31
+ More information needed
32
+
33
+ ## Intended uses & limitations
34
+
35
+ More information needed
36
+
37
+ ## Training and evaluation data
38
+
39
+ More information needed
40
+
41
+ ## Training procedure
42
+
43
+ ### Training hyperparameters
44
+
45
+ The following hyperparameters were used during training:
46
+ - learning_rate: 2e-05
47
+ - train_batch_size: 8
48
+ - eval_batch_size: 8
49
+ - seed: 8569382
50
+ - distributed_type: multi-GPU
51
+ - num_devices: 4
52
+ - gradient_accumulation_steps: 2
53
+ - total_train_batch_size: 64
54
+ - total_eval_batch_size: 32
55
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
56
+ - lr_scheduler_type: cosine
57
+ - lr_scheduler_warmup_ratio: 0.1
58
+ - num_epochs: 1
59
+
60
+ ### Training results
61
+
62
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
63
+ |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
64
+ | No log | 0 | 0 | 0.4941 | 0.7546 | 0.6364 | 0.2526 | 0.3616 |
65
+ | 0.483 | 0.0169 | 20 | 0.4898 | 0.7645 | 0.7 | 0.2526 | 0.3712 |
66
+ | 0.5491 | 0.0339 | 40 | 0.4646 | 0.7716 | 0.7705 | 0.2423 | 0.3686 |
67
+ | 0.3868 | 0.0508 | 60 | 0.3927 | 0.8014 | 0.8462 | 0.3402 | 0.4853 |
68
+ | 0.2752 | 0.0678 | 80 | 0.2430 | 0.9149 | 0.9589 | 0.7216 | 0.8235 |
69
+ | 0.1319 | 0.0847 | 100 | 0.0990 | 0.9716 | 0.9531 | 0.9433 | 0.9482 |
70
+ | 0.0971 | 0.1017 | 120 | 0.0422 | 0.9915 | 0.9747 | 0.9948 | 0.9847 |
71
+ | 0.0478 | 0.1186 | 140 | 0.0120 | 0.9986 | 1.0 | 0.9948 | 0.9974 |
72
+ | 0.0373 | 0.1356 | 160 | 0.0099 | 0.9986 | 1.0 | 0.9948 | 0.9974 |
73
+ | 0.0357 | 0.1525 | 180 | 0.0073 | 0.9972 | 0.9948 | 0.9948 | 0.9948 |
74
+ | 0.0147 | 0.1695 | 200 | 0.0105 | 0.9986 | 1.0 | 0.9948 | 0.9974 |
75
+ | 0.0271 | 0.1864 | 220 | 0.0075 | 0.9986 | 1.0 | 0.9948 | 0.9974 |
76
+ | 0.0071 | 0.2034 | 240 | 0.0073 | 0.9986 | 1.0 | 0.9948 | 0.9974 |
77
+ | 0.009 | 0.2203 | 260 | 0.0021 | 1.0 | 1.0 | 1.0 | 1.0 |
78
+ | 0.0288 | 0.2373 | 280 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
79
+ | 0.0236 | 0.2542 | 300 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
80
+ | 0.0053 | 0.2712 | 320 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
81
+ | 0.0028 | 0.2881 | 340 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
82
+ | 0.015 | 0.3051 | 360 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
83
+ | 0.0446 | 0.3220 | 380 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
84
+ | 0.0261 | 0.3390 | 400 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
85
+ | 0.0032 | 0.3559 | 420 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
86
+ | 0.0413 | 0.3729 | 440 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
87
+ | 0.0189 | 0.3898 | 460 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
88
+ | 0.003 | 0.4068 | 480 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
89
+ | 0.0071 | 0.4237 | 500 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
90
+ | 0.0139 | 0.4407 | 520 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
91
+ | 0.0161 | 0.4576 | 540 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
92
+ | 0.0027 | 0.4746 | 560 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
93
+ | 0.0039 | 0.4915 | 580 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
94
+ | 0.0067 | 0.5085 | 600 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
95
+ | 0.012 | 0.5254 | 620 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
96
+ | 0.006 | 0.5424 | 640 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
97
+ | 0.0025 | 0.5593 | 660 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
98
+ | 0.0055 | 0.5763 | 680 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
99
+ | 0.0116 | 0.5932 | 700 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
100
+ | 0.014 | 0.6102 | 720 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
101
+ | 0.0042 | 0.6271 | 740 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
102
+ | 0.0418 | 0.6441 | 760 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
103
+ | 0.0024 | 0.6610 | 780 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
104
+ | 0.0039 | 0.6780 | 800 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
105
+ | 0.0048 | 0.6949 | 820 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
106
+ | 0.0007 | 0.7119 | 840 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
107
+ | 0.0014 | 0.7288 | 860 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
108
+ | 0.0056 | 0.7458 | 880 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
109
+ | 0.0107 | 0.7627 | 900 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
110
+ | 0.0027 | 0.7797 | 920 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
111
+ | 0.0105 | 0.7966 | 940 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
112
+ | 0.0157 | 0.8136 | 960 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
113
+ | 0.0082 | 0.8305 | 980 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
114
+ | 0.0084 | 0.8475 | 1000 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
115
+ | 0.0182 | 0.8644 | 1020 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
116
+ | 0.0053 | 0.8814 | 1040 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
117
+ | 0.0087 | 0.8983 | 1060 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
118
+ | 0.0017 | 0.9153 | 1080 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
119
+ | 0.0058 | 0.9322 | 1100 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
120
+ | 0.0015 | 0.9492 | 1120 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
121
+ | 0.0059 | 0.9661 | 1140 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
122
+ | 0.0069 | 0.9831 | 1160 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
123
+ | 0.0058 | 1.0 | 1180 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
124
+
125
+
126
+ ### Framework versions
127
+
128
+ - PEFT 0.13.2
129
+ - Transformers 4.46.0
130
+ - Pytorch 2.5.1+cu124
131
+ - Datasets 3.1.0
132
+ - Tokenizers 0.20.3
adapter_config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "peiyi9979/math-shepherd-mistral-7b-prm",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.05,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 16,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "q_proj",
24
+ "v_proj"
25
+ ],
26
+ "task_type": "CAUSAL_LM",
27
+ "use_dora": false,
28
+ "use_rslora": false
29
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e4e94fafcca231f8b92aae6e9273e5bb4d92e688669b6319a7129481a9c401a9
3
+ size 27280152