lamaabdulaziz commited on
Commit
815a89d
1 Parent(s): 1b0c0af

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +67 -0
README.md ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ metrics:
5
+ - accuracy
6
+ - precision
7
+ - recall
8
+ model-index:
9
+ - name: AraBERT-finetuned-CrossVal-fnd
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
+ # AraBERT-finetuned-CrossVal-fnd
17
+
18
+ This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.2667
21
+ - Macro F1: 0.8831
22
+ - Accuracy: 0.8867
23
+ - Precision: 0.8826
24
+ - Recall: 0.8837
25
+
26
+ ## Model description
27
+
28
+ More information needed
29
+
30
+ ## Intended uses & limitations
31
+
32
+ More information needed
33
+
34
+ ## Training and evaluation data
35
+
36
+ More information needed
37
+
38
+ ## Training procedure
39
+
40
+ ### Training hyperparameters
41
+
42
+ The following hyperparameters were used during training:
43
+ - learning_rate: 2e-05
44
+ - train_batch_size: 16
45
+ - eval_batch_size: 32
46
+ - seed: 123
47
+ - gradient_accumulation_steps: 2
48
+ - total_train_batch_size: 32
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - num_epochs: 4
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
56
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
57
+ | 0.296 | 1.0 | 798 | 0.2754 | 0.8729 | 0.8786 | 0.8795 | 0.8684 |
58
+ | 0.2126 | 2.0 | 1596 | 0.2667 | 0.8831 | 0.8867 | 0.8826 | 0.8837 |
59
+ | 0.1719 | 3.0 | 2394 | 0.3204 | 0.8780 | 0.8815 | 0.8768 | 0.8794 |
60
+
61
+
62
+ ### Framework versions
63
+
64
+ - Transformers 4.20.1
65
+ - Pytorch 1.11.0
66
+ - Datasets 2.1.0
67
+ - Tokenizers 0.12.1