ironrock commited on
Commit
0b4e9b7
1 Parent(s): 49c6615

Model save

Browse files
Files changed (1) hide show
  1. README.md +80 -0
README.md ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ library_name: peft
4
+ tags:
5
+ - trl
6
+ - sft
7
+ - generated_from_trainer
8
+ base_model: mistralai/Mistral-7B-Instruct-v0.2
9
+ model-index:
10
+ - name: ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # ZeroShot-3.3.25-Mistral-7b-Multilanguage-3.2.0
18
+
19
+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.0503
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 0.0002
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 2
43
+ - seed: 42
44
+ - gradient_accumulation_steps: 2
45
+ - total_train_batch_size: 16
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: cosine
48
+ - lr_scheduler_warmup_ratio: 0.1
49
+ - num_epochs: 1
50
+ - mixed_precision_training: Native AMP
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss |
55
+ |:-------------:|:-----:|:----:|:---------------:|
56
+ | 0.1409 | 0.06 | 100 | 0.0993 |
57
+ | 0.0916 | 0.12 | 200 | 0.0877 |
58
+ | 0.0965 | 0.19 | 300 | 0.0970 |
59
+ | 0.0933 | 0.25 | 400 | 0.0898 |
60
+ | 0.0776 | 0.31 | 500 | 0.0749 |
61
+ | 0.0793 | 0.37 | 600 | 0.0850 |
62
+ | 0.0768 | 0.43 | 700 | 0.0701 |
63
+ | 0.0597 | 0.5 | 800 | 0.0767 |
64
+ | 0.0648 | 0.56 | 900 | 0.0766 |
65
+ | 0.0635 | 0.62 | 1000 | 0.0649 |
66
+ | 0.0536 | 0.68 | 1100 | 0.0641 |
67
+ | 0.0511 | 0.74 | 1200 | 0.0559 |
68
+ | 0.0638 | 0.81 | 1300 | 0.0507 |
69
+ | 0.0462 | 0.87 | 1400 | 0.0512 |
70
+ | 0.0494 | 0.93 | 1500 | 0.0507 |
71
+ | 0.0457 | 0.99 | 1600 | 0.0503 |
72
+
73
+
74
+ ### Framework versions
75
+
76
+ - PEFT 0.9.0
77
+ - Transformers 4.38.2
78
+ - Pytorch 2.1.0+cu121
79
+ - Datasets 2.18.0
80
+ - Tokenizers 0.15.2