grace-pro commited on
Commit
bcf967a
1 Parent(s): 6ff0e85

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +68 -0
README.md ADDED
@@ -0,0 +1,68 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: Davlan/afro-xlmr-base
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - precision
8
+ - recall
9
+ - f1
10
+ - accuracy
11
+ model-index:
12
+ - name: no-deletion-3
13
+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
+ should probably proofread and complete it, then remove this comment. -->
18
+
19
+ # no-deletion-3
20
+
21
+ This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: 0.1208
24
+ - Precision: 0.7219
25
+ - Recall: 0.5650
26
+ - F1: 0.6339
27
+ - Accuracy: 0.9636
28
+
29
+ ## Model description
30
+
31
+ More information needed
32
+
33
+ ## Intended uses & limitations
34
+
35
+ More information needed
36
+
37
+ ## Training and evaluation data
38
+
39
+ More information needed
40
+
41
+ ## Training procedure
42
+
43
+ ### Training hyperparameters
44
+
45
+ The following hyperparameters were used during training:
46
+ - learning_rate: 5e-05
47
+ - train_batch_size: 16
48
+ - eval_batch_size: 8
49
+ - seed: 42
50
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
+ - lr_scheduler_type: linear
52
+ - num_epochs: 3
53
+
54
+ ### Training results
55
+
56
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
57
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
58
+ | 0.1473 | 1.0 | 1312 | 0.1226 | 0.6686 | 0.5042 | 0.5749 | 0.9577 |
59
+ | 0.1076 | 2.0 | 2624 | 0.1202 | 0.7201 | 0.5375 | 0.6155 | 0.9622 |
60
+ | 0.0816 | 3.0 | 3936 | 0.1208 | 0.7219 | 0.5650 | 0.6339 | 0.9636 |
61
+
62
+
63
+ ### Framework versions
64
+
65
+ - Transformers 4.31.0
66
+ - Pytorch 2.0.1+cu118
67
+ - Datasets 2.13.1
68
+ - Tokenizers 0.13.3