Hugging Face's logo

hou
/
translation-model

Text2Text Generation
Transformers
PyTorch
TensorBoard
m2m_100
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
1
hou commited on
Commit
883b9ce
·
1 Parent(s): 8a24cdb

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +100 -0
README.md ADDED
@@ -0,0 +1,100 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-nc-4.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - bleu
7
+ model-index:
8
+ - name: NLLB-alt-cv-bleu-40
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
+ # NLLB-alt-cv-bleu-40
16
+
17
+ This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.7734
20
+ - Bleu: 30.3568
21
+ - Gen Len: 50.699
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: 0.0001
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 8
43
+ - seed: 42
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 40
47
+ - mixed_precision_training: Native AMP
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
52
+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
53
+ | 2.1031 | 1.0 | 1380 | 1.6725 | 6.1774 | 56.292 |
54
+ | 1.4925 | 2.0 | 2760 | 1.3799 | 8.9414 | 54.966 |
55
+ | 1.1976 | 3.0 | 4140 | 1.2417 | 10.7993 | 55.32 |
56
+ | 0.9973 | 4.0 | 5520 | 1.1744 | 13.7633 | 51.225 |
57
+ | 0.8305 | 5.0 | 6900 | 1.1461 | 14.8273 | 51.723 |
58
+ | 0.6918 | 6.0 | 8280 | 1.1261 | 16.02 | 50.83 |
59
+ | 0.5823 | 7.0 | 9660 | 1.1556 | 17.8129 | 49.93 |
60
+ | 0.4934 | 8.0 | 11040 | 1.1567 | 19.3213 | 50.647 |
61
+ | 0.4049 | 9.0 | 12420 | 1.1794 | 21.712 | 50.722 |
62
+ | 0.3342 | 10.0 | 13800 | 1.2320 | 22.2956 | 50.552 |
63
+ | 0.2747 | 11.0 | 15180 | 1.2749 | 24.3631 | 50.443 |
64
+ | 0.2281 | 12.0 | 16560 | 1.2996 | 25.4046 | 52.437 |
65
+ | 0.1849 | 13.0 | 17940 | 1.3378 | 26.5399 | 50.361 |
66
+ | 0.153 | 14.0 | 19320 | 1.3709 | 27.0563 | 51.077 |
67
+ | 0.1256 | 15.0 | 20700 | 1.4128 | 27.8781 | 51.129 |
68
+ | 0.1103 | 16.0 | 22080 | 1.4354 | 28.6894 | 51.974 |
69
+ | 0.0893 | 17.0 | 23460 | 1.4859 | 28.0852 | 52.005 |
70
+ | 0.0778 | 18.0 | 24840 | 1.4973 | 28.9053 | 50.803 |
71
+ | 0.0683 | 19.0 | 26220 | 1.5294 | 29.2219 | 50.845 |
72
+ | 0.0592 | 20.0 | 27600 | 1.5576 | 29.1227 | 51.051 |
73
+ | 0.0505 | 21.0 | 28980 | 1.5885 | 29.4121 | 50.376 |
74
+ | 0.0441 | 22.0 | 30360 | 1.6028 | 29.5531 | 51.946 |
75
+ | 0.0397 | 23.0 | 31740 | 1.6254 | 29.3607 | 50.811 |
76
+ | 0.0361 | 24.0 | 33120 | 1.6374 | 29.5197 | 51.166 |
77
+ | 0.0323 | 25.0 | 34500 | 1.6423 | 29.7589 | 51.335 |
78
+ | 0.0288 | 26.0 | 35880 | 1.6630 | 29.6029 | 51.036 |
79
+ | 0.0257 | 27.0 | 37260 | 1.6800 | 29.4437 | 50.623 |
80
+ | 0.0235 | 28.0 | 38640 | 1.6887 | 29.9344 | 50.797 |
81
+ | 0.0201 | 29.0 | 40020 | 1.7096 | 30.1522 | 50.694 |
82
+ | 0.018 | 30.0 | 41400 | 1.7223 | 30.1291 | 50.425 |
83
+ | 0.0163 | 31.0 | 42780 | 1.7282 | 29.8131 | 51.114 |
84
+ | 0.0148 | 32.0 | 44160 | 1.7299 | 29.9721 | 50.851 |
85
+ | 0.0133 | 33.0 | 45540 | 1.7463 | 30.0369 | 50.477 |
86
+ | 0.0122 | 34.0 | 46920 | 1.7514 | 30.0663 | 51.133 |
87
+ | 0.0112 | 35.0 | 48300 | 1.7508 | 30.0451 | 50.736 |
88
+ | 0.0099 | 36.0 | 49680 | 1.7631 | 30.0576 | 50.62 |
89
+ | 0.0087 | 37.0 | 51060 | 1.7683 | 30.1648 | 50.874 |
90
+ | 0.0083 | 38.0 | 52440 | 1.7750 | 30.2558 | 50.667 |
91
+ | 0.0076 | 39.0 | 53820 | 1.7757 | 30.3551 | 50.886 |
92
+ | 0.0076 | 40.0 | 55200 | 1.7734 | 30.3568 | 50.699 |
93
+
94
+
95
+ ### Framework versions
96
+
97
+ - Transformers 4.21.0
98
+ - Pytorch 1.10.0+cu113
99
+ - Datasets 2.4.0
100
+ - Tokenizers 0.12.1