Hugging Face's logo

SkyR
/
hing-mbert-ours-run-2

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
1
SkyR commited on
Commit
5a094b2
•
1 Parent(s): d50a6bd

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +83 -0
README.md ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-4.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ - precision
8
+ - recall
9
+ - f1
10
+ model-index:
11
+ - name: hing-mbert-ours-run-2
12
+ results: []
13
+ ---
14
+
15
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
16
+ should probably proofread and complete it, then remove this comment. -->
17
+
18
+ # hing-mbert-ours-run-2
19
+
20
+ This model is a fine-tuned version of [l3cube-pune/hing-mbert](https://huggingface.co/l3cube-pune/hing-mbert) on an unknown dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 3.3919
23
+ - Accuracy: 0.62
24
+ - Precision: 0.5759
25
+ - Recall: 0.5631
26
+ - F1: 0.5669
27
+
28
+ ## Model description
29
+
30
+ More information needed
31
+
32
+ ## Intended uses & limitations
33
+
34
+ More information needed
35
+
36
+ ## Training and evaluation data
37
+
38
+ More information needed
39
+
40
+ ## Training procedure
41
+
42
+ ### Training hyperparameters
43
+
44
+ The following hyperparameters were used during training:
45
+ - learning_rate: 5e-05
46
+ - train_batch_size: 16
47
+ - eval_batch_size: 16
48
+ - seed: 42
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - num_epochs: 20
52
+
53
+ ### Training results
54
+
55
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
56
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
57
+ | 1.0284 | 1.0 | 100 | 1.2914 | 0.595 | 0.5712 | 0.4800 | 0.4642 |
58
+ | 0.8127 | 2.0 | 200 | 0.8552 | 0.59 | 0.5744 | 0.5675 | 0.4891 |
59
+ | 0.5499 | 3.0 | 300 | 1.1212 | 0.645 | 0.6544 | 0.5600 | 0.5475 |
60
+ | 0.3433 | 4.0 | 400 | 1.2017 | 0.605 | 0.5872 | 0.5866 | 0.5791 |
61
+ | 0.2218 | 5.0 | 500 | 1.8329 | 0.655 | 0.6458 | 0.6064 | 0.6055 |
62
+ | 0.1763 | 6.0 | 600 | 2.4194 | 0.655 | 0.6140 | 0.5802 | 0.5871 |
63
+ | 0.1022 | 7.0 | 700 | 2.3894 | 0.66 | 0.6171 | 0.6045 | 0.6048 |
64
+ | 0.0631 | 8.0 | 800 | 2.8259 | 0.605 | 0.5704 | 0.5255 | 0.5259 |
65
+ | 0.0254 | 9.0 | 900 | 2.9135 | 0.65 | 0.6013 | 0.5734 | 0.5784 |
66
+ | 0.0316 | 10.0 | 1000 | 3.0548 | 0.62 | 0.5862 | 0.5650 | 0.5670 |
67
+ | 0.026 | 11.0 | 1100 | 3.1020 | 0.62 | 0.5722 | 0.5593 | 0.5619 |
68
+ | 0.0152 | 12.0 | 1200 | 3.0692 | 0.62 | 0.5685 | 0.5597 | 0.5621 |
69
+ | 0.0156 | 13.0 | 1300 | 3.1068 | 0.615 | 0.5771 | 0.5589 | 0.5624 |
70
+ | 0.0237 | 14.0 | 1400 | 3.3487 | 0.62 | 0.5924 | 0.5589 | 0.5642 |
71
+ | 0.0094 | 15.0 | 1500 | 3.2007 | 0.615 | 0.5665 | 0.5639 | 0.5650 |
72
+ | 0.0054 | 16.0 | 1600 | 3.2838 | 0.62 | 0.5807 | 0.5657 | 0.5690 |
73
+ | 0.005 | 17.0 | 1700 | 3.2258 | 0.615 | 0.5846 | 0.5723 | 0.5747 |
74
+ | 0.005 | 18.0 | 1800 | 3.3572 | 0.63 | 0.5827 | 0.5698 | 0.5736 |
75
+ | 0.0022 | 19.0 | 1900 | 3.3642 | 0.62 | 0.5759 | 0.5631 | 0.5669 |
76
+ | 0.0019 | 20.0 | 2000 | 3.3919 | 0.62 | 0.5759 | 0.5631 | 0.5669 |
77
+
78
+
79
+ ### Framework versions
80
+
81
+ - Transformers 4.25.1
82
+ - Pytorch 1.13.0+cu116
83
+ - Tokenizers 0.13.2