ncduy commited on
Commit
bcaae13
1 Parent(s): b33ae05

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +63 -0
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - bleu
7
+ model-index:
8
+ - name: opus-mt-en-vi-own-finetuned-en-to-vi
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
+ # opus-mt-en-vi-own-finetuned-en-to-vi
16
+
17
+ This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-vi](https://huggingface.co/Helsinki-NLP/opus-mt-en-vi) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 5.4416
20
+ - Bleu: 2.1189
21
+ - Gen Len: 25.153
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: 2e-05
41
+ - train_batch_size: 64
42
+ - eval_batch_size: 64
43
+ - seed: 42
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 3
47
+ - mixed_precision_training: Native AMP
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
52
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
53
+ | 6.2513 | 1.0 | 1563 | 6.0147 | 0.7038 | 29.165 |
54
+ | 5.7184 | 2.0 | 3126 | 5.5631 | 1.9803 | 23.915 |
55
+ | 5.5248 | 3.0 | 4689 | 5.4416 | 2.1189 | 25.153 |
56
+
57
+
58
+ ### Framework versions
59
+
60
+ - Transformers 4.15.0
61
+ - Pytorch 1.10.0+cu111
62
+ - Datasets 1.17.0
63
+ - Tokenizers 0.10.3