MM2157 commited on
Commit
8f9399f
1 Parent(s): 677a58a

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +73 -0
README.md ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ metrics:
5
+ - precision
6
+ - recall
7
+ - f1
8
+ - accuracy
9
+ model-index:
10
+ - name: AraBERT_token_classification_AraEval24_18_labels_augmented_fixed2
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
+ # AraBERT_token_classification_AraEval24_18_labels_augmented_fixed2
18
+
19
+ This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.8169
22
+ - Precision: 0.0952
23
+ - Recall: 0.0280
24
+ - F1: 0.0432
25
+ - Accuracy: 0.8714
26
+
27
+ ## Model description
28
+
29
+ More information needed
30
+
31
+ ## Intended uses & limitations
32
+
33
+ More information needed
34
+
35
+ ## Training and evaluation data
36
+
37
+ More information needed
38
+
39
+ ## Training procedure
40
+
41
+ ### Training hyperparameters
42
+
43
+ The following hyperparameters were used during training:
44
+ - learning_rate: 2e-05
45
+ - train_batch_size: 8
46
+ - eval_batch_size: 8
47
+ - seed: 42
48
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
+ - lr_scheduler_type: linear
50
+ - num_epochs: 10
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
55
+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
56
+ | 0.684 | 1.0 | 3215 | 0.7004 | 0.0 | 0.0 | 0.0 | 0.8767 |
57
+ | 0.5935 | 2.0 | 6430 | 0.6946 | 0.0909 | 0.0005 | 0.0010 | 0.8765 |
58
+ | 0.5262 | 3.0 | 9645 | 0.7115 | 0.0952 | 0.0097 | 0.0176 | 0.8755 |
59
+ | 0.4585 | 4.0 | 12860 | 0.7140 | 0.0788 | 0.0204 | 0.0324 | 0.8718 |
60
+ | 0.4415 | 5.0 | 16075 | 0.7314 | 0.0982 | 0.0104 | 0.0188 | 0.8750 |
61
+ | 0.39 | 6.0 | 19290 | 0.7542 | 0.0942 | 0.0167 | 0.0284 | 0.8734 |
62
+ | 0.3668 | 7.0 | 22505 | 0.7570 | 0.0947 | 0.0230 | 0.0371 | 0.8721 |
63
+ | 0.3314 | 8.0 | 25720 | 0.8040 | 0.0887 | 0.0290 | 0.0437 | 0.8712 |
64
+ | 0.308 | 9.0 | 28935 | 0.7975 | 0.0977 | 0.0295 | 0.0454 | 0.8714 |
65
+ | 0.3007 | 10.0 | 32150 | 0.8169 | 0.0952 | 0.0280 | 0.0432 | 0.8714 |
66
+
67
+
68
+ ### Framework versions
69
+
70
+ - Transformers 4.30.2
71
+ - Pytorch 1.12.1
72
+ - Datasets 2.13.2
73
+ - Tokenizers 0.13.3