Hugging Face's logo

Ashley37sky
/
qwen_checkpoints

PEFT
Safetensors
Generated from Trainer
Model card Files
xet
Community
1

Improve language tag

#1
by lbourdois - opened
base: refs/heads/main
←
from: refs/pr/1
Discussion Files changed
+95
-81
Files changed (1) hide show
  1. README.md +95 -81
README.md CHANGED
@@ -1,82 +1,96 @@
1
- ---
2
- library_name: peft
3
- license: apache-2.0
4
- base_model: Qwen/Qwen2.5-1.5B-Instruct
5
- tags:
6
- - generated_from_trainer
7
- model-index:
8
- - name: qwen_checkpoints
9
- results: []
10
- ---
11
-
12
- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
- should probably proofread and complete it, then remove this comment. -->
14
-
15
- # qwen_checkpoints
16
-
17
- This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on an unknown dataset.
18
- It achieves the following results on the evaluation set:
19
- - Loss: 0.0618
20
- - Mse: 0.0618
21
- - Mae: 0.1983
22
- - R Squared: 0.3107
23
-
24
- ## Model description
25
-
26
- More information needed
27
-
28
- ## Intended uses & limitations
29
-
30
- More information needed
31
-
32
- ## Training and evaluation data
33
-
34
- More information needed
35
-
36
- ## Training procedure
37
-
38
- ### Training hyperparameters
39
-
40
- The following hyperparameters were used during training:
41
- - learning_rate: 0.0001
42
- - train_batch_size: 64
43
- - eval_batch_size: 64
44
- - seed: 42
45
- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
- - lr_scheduler_type: cosine
47
- - lr_scheduler_warmup_ratio: 0.01
48
- - num_epochs: 3
49
- - mixed_precision_training: Native AMP
50
-
51
- ### Training results
52
-
53
- | Training Loss | Epoch | Step | Validation Loss | Mae | Mse | R Squared |
54
- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:|
55
- | 0.0856 | 0.1558 | 100 | 0.0878 | 0.2351 | 0.0878 | 0.0207 |
56
- | 0.0843 | 0.3115 | 200 | 0.0803 | 0.2314 | 0.0803 | 0.1045 |
57
- | 0.0851 | 0.4673 | 300 | 0.0882 | 0.2278 | 0.0882 | 0.0168 |
58
- | 0.0676 | 0.6231 | 400 | 0.0716 | 0.2183 | 0.0716 | 0.2014 |
59
- | 0.0737 | 0.7788 | 500 | 0.0691 | 0.2164 | 0.0691 | 0.2291 |
60
- | 0.0694 | 0.9346 | 600 | 0.0696 | 0.2157 | 0.0696 | 0.2242 |
61
- | 0.0569 | 1.0903 | 700 | 0.0661 | 0.2049 | 0.0661 | 0.2627 |
62
- | 0.0589 | 1.2461 | 800 | 0.0663 | 0.2045 | 0.0663 | 0.2606 |
63
- | 0.0648 | 1.4019 | 900 | 0.0649 | 0.2039 | 0.0649 | 0.2764 |
64
- | 0.0652 | 1.5576 | 1000 | 0.0644 | 0.2027 | 0.0644 | 0.2813 |
65
- | 0.0657 | 1.7134 | 1100 | 0.0649 | 0.0649 | 0.2082 | 0.2763 |
66
- | 0.0577 | 1.8692 | 1200 | 0.0639 | 0.0639 | 0.2022 | 0.2869 |
67
- | 0.0564 | 2.0249 | 1300 | 0.0636 | 0.0636 | 0.2006 | 0.2902 |
68
- | 0.0613 | 2.1807 | 1400 | 0.0633 | 0.0633 | 0.1989 | 0.2939 |
69
- | 0.0596 | 2.3364 | 1500 | 0.0624 | 0.0624 | 0.1999 | 0.3036 |
70
- | 0.0547 | 2.4922 | 1600 | 0.0621 | 0.0621 | 0.1985 | 0.3076 |
71
- | 0.0554 | 2.6480 | 1700 | 0.0620 | 0.0620 | 0.1974 | 0.3087 |
72
- | 0.0581 | 2.8037 | 1800 | 0.0618 | 0.0618 | 0.1983 | 0.3107 |
73
- | 0.0653 | 2.9595 | 1900 | 0.0618 | 0.0618 | 0.1983 | 0.3107 |
74
-
75
-
76
- ### Framework versions
77
-
78
- - PEFT 0.13.2
79
- - Transformers 4.45.2
80
- - Pytorch 2.5.1+cu121
81
- - Datasets 3.1.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
  - Tokenizers 0.20.3
 
1
+ ---
2
+ library_name: peft
3
+ license: apache-2.0
4
+ base_model: Qwen/Qwen2.5-1.5B-Instruct
5
+ tags:
6
+ - generated_from_trainer
7
+ language:
8
+ - zho
9
+ - eng
10
+ - fra
11
+ - spa
12
+ - por
13
+ - deu
14
+ - ita
15
+ - rus
16
+ - jpn
17
+ - kor
18
+ - vie
19
+ - tha
20
+ - ara
21
+ model-index:
22
+ - name: qwen_checkpoints
23
+ results: []
24
+ ---
25
+
26
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
27
+ should probably proofread and complete it, then remove this comment. -->
28
+
29
+ # qwen_checkpoints
30
+
31
+ This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on an unknown dataset.
32
+ It achieves the following results on the evaluation set:
33
+ - Loss: 0.0618
34
+ - Mse: 0.0618
35
+ - Mae: 0.1983
36
+ - R Squared: 0.3107
37
+
38
+ ## Model description
39
+
40
+ More information needed
41
+
42
+ ## Intended uses & limitations
43
+
44
+ More information needed
45
+
46
+ ## Training and evaluation data
47
+
48
+ More information needed
49
+
50
+ ## Training procedure
51
+
52
+ ### Training hyperparameters
53
+
54
+ The following hyperparameters were used during training:
55
+ - learning_rate: 0.0001
56
+ - train_batch_size: 64
57
+ - eval_batch_size: 64
58
+ - seed: 42
59
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
60
+ - lr_scheduler_type: cosine
61
+ - lr_scheduler_warmup_ratio: 0.01
62
+ - num_epochs: 3
63
+ - mixed_precision_training: Native AMP
64
+
65
+ ### Training results
66
+
67
+ | Training Loss | Epoch | Step | Validation Loss | Mae | Mse | R Squared |
68
+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:|
69
+ | 0.0856 | 0.1558 | 100 | 0.0878 | 0.2351 | 0.0878 | 0.0207 |
70
+ | 0.0843 | 0.3115 | 200 | 0.0803 | 0.2314 | 0.0803 | 0.1045 |
71
+ | 0.0851 | 0.4673 | 300 | 0.0882 | 0.2278 | 0.0882 | 0.0168 |
72
+ | 0.0676 | 0.6231 | 400 | 0.0716 | 0.2183 | 0.0716 | 0.2014 |
73
+ | 0.0737 | 0.7788 | 500 | 0.0691 | 0.2164 | 0.0691 | 0.2291 |
74
+ | 0.0694 | 0.9346 | 600 | 0.0696 | 0.2157 | 0.0696 | 0.2242 |
75
+ | 0.0569 | 1.0903 | 700 | 0.0661 | 0.2049 | 0.0661 | 0.2627 |
76
+ | 0.0589 | 1.2461 | 800 | 0.0663 | 0.2045 | 0.0663 | 0.2606 |
77
+ | 0.0648 | 1.4019 | 900 | 0.0649 | 0.2039 | 0.0649 | 0.2764 |
78
+ | 0.0652 | 1.5576 | 1000 | 0.0644 | 0.2027 | 0.0644 | 0.2813 |
79
+ | 0.0657 | 1.7134 | 1100 | 0.0649 | 0.0649 | 0.2082 | 0.2763 |
80
+ | 0.0577 | 1.8692 | 1200 | 0.0639 | 0.0639 | 0.2022 | 0.2869 |
81
+ | 0.0564 | 2.0249 | 1300 | 0.0636 | 0.0636 | 0.2006 | 0.2902 |
82
+ | 0.0613 | 2.1807 | 1400 | 0.0633 | 0.0633 | 0.1989 | 0.2939 |
83
+ | 0.0596 | 2.3364 | 1500 | 0.0624 | 0.0624 | 0.1999 | 0.3036 |
84
+ | 0.0547 | 2.4922 | 1600 | 0.0621 | 0.0621 | 0.1985 | 0.3076 |
85
+ | 0.0554 | 2.6480 | 1700 | 0.0620 | 0.0620 | 0.1974 | 0.3087 |
86
+ | 0.0581 | 2.8037 | 1800 | 0.0618 | 0.0618 | 0.1983 | 0.3107 |
87
+ | 0.0653 | 2.9595 | 1900 | 0.0618 | 0.0618 | 0.1983 | 0.3107 |
88
+
89
+
90
+ ### Framework versions
91
+
92
+ - PEFT 0.13.2
93
+ - Transformers 4.45.2
94
+ - Pytorch 2.5.1+cu121
95
+ - Datasets 3.1.0
96
  - Tokenizers 0.20.3