Shularp commited on
Commit
39891d3
1 Parent(s): a91daca

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
+ - translation
5
+ - generated_from_trainer
6
+ metrics:
7
+ - bleu
8
+ model-index:
9
+ - name: model-translate-ar-to-en-from-120k-dataset-ar-en-th230111752
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # model-translate-ar-to-en-from-120k-dataset-ar-en-th230111752
17
+
18
+ This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the None dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 1.2879
21
+ - Bleu: 36.3711
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: 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: 3
47
+ - mixed_precision_training: Native AMP
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Bleu |
52
+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|
53
+ | 1.3225 | 1.0 | 12500 | 1.3048 | 35.6396 |
54
+ | 1.0963 | 2.0 | 25000 | 1.2906 | 36.2535 |
55
+ | 1.1074 | 3.0 | 37500 | 1.2879 | 36.3711 |
56
+
57
+
58
+ ### Framework versions
59
+
60
+ - Transformers 4.25.1
61
+ - Pytorch 1.13.0+cu116
62
+ - Datasets 2.8.0
63
+ - Tokenizers 0.13.2