Hugging Face's logo

Zahra99
/
bert-base-uncased-finetuned-iemocap8

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
1
Zahra99 commited on
Commit
5db1f72
·
1 Parent(s): 24887c8

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +90 -0
README.md ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ - f1
8
+ model-index:
9
+ - name: bert-base-uncased-finetuned-iemocap8
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
+ # bert-base-uncased-finetuned-iemocap8
17
+
18
+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 1.8968
21
+ - Accuracy: 0.6654
22
+ - F1: 0.6723
23
+
24
+ ## Model description
25
+
26
+ More information needed
27
+
28
+ ## Intended uses & limitations
29
+
30
+ More information needed
31
+
32
+ ## Training and evaluation data
33
+
34
+ More information needed
35
+
36
+ ## Training procedure
37
+
38
+ ### Training hyperparameters
39
+
40
+ The following hyperparameters were used during training:
41
+ - learning_rate: 4.319412088241492e-05
42
+ - train_batch_size: 64
43
+ - eval_batch_size: 32
44
+ - seed: 42
45
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
+ - lr_scheduler_type: linear
47
+ - num_epochs: 30
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
52
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
53
+ | No log | 1.0 | 51 | 1.0531 | 0.5597 | 0.5655 |
54
+ | 1.0284 | 2.0 | 102 | 0.9370 | 0.6227 | 0.6304 |
55
+ | 1.0284 | 3.0 | 153 | 0.8796 | 0.6722 | 0.6765 |
56
+ | 0.4432 | 4.0 | 204 | 0.9785 | 0.6654 | 0.6727 |
57
+ | 0.4432 | 5.0 | 255 | 1.0664 | 0.6586 | 0.6634 |
58
+ | 0.2492 | 6.0 | 306 | 1.1291 | 0.6499 | 0.6606 |
59
+ | 0.2492 | 7.0 | 357 | 1.1847 | 0.6702 | 0.6777 |
60
+ | 0.1707 | 8.0 | 408 | 1.4084 | 0.6508 | 0.6534 |
61
+ | 0.1707 | 9.0 | 459 | 1.3468 | 0.6702 | 0.6762 |
62
+ | 0.1461 | 10.0 | 510 | 1.4245 | 0.6634 | 0.6710 |
63
+ | 0.1461 | 11.0 | 561 | 1.4865 | 0.6499 | 0.6600 |
64
+ | 0.1262 | 12.0 | 612 | 1.4616 | 0.6576 | 0.6656 |
65
+ | 0.1262 | 13.0 | 663 | 1.5335 | 0.6663 | 0.6711 |
66
+ | 0.1203 | 14.0 | 714 | 1.4855 | 0.6731 | 0.6806 |
67
+ | 0.1203 | 15.0 | 765 | 1.5825 | 0.6712 | 0.6792 |
68
+ | 0.1023 | 16.0 | 816 | 1.7145 | 0.6731 | 0.6794 |
69
+ | 0.1023 | 17.0 | 867 | 1.6676 | 0.6751 | 0.6823 |
70
+ | 0.0976 | 18.0 | 918 | 1.8013 | 0.6693 | 0.6719 |
71
+ | 0.0976 | 19.0 | 969 | 1.7192 | 0.6673 | 0.6755 |
72
+ | 0.0937 | 20.0 | 1020 | 1.7837 | 0.6654 | 0.6731 |
73
+ | 0.0937 | 21.0 | 1071 | 1.7779 | 0.6760 | 0.6831 |
74
+ | 0.0901 | 22.0 | 1122 | 1.8352 | 0.6615 | 0.6687 |
75
+ | 0.0901 | 23.0 | 1173 | 1.8601 | 0.6596 | 0.6656 |
76
+ | 0.0844 | 24.0 | 1224 | 1.9129 | 0.6625 | 0.6719 |
77
+ | 0.0844 | 25.0 | 1275 | 1.8507 | 0.6731 | 0.6784 |
78
+ | 0.0829 | 26.0 | 1326 | 1.8582 | 0.6673 | 0.6735 |
79
+ | 0.0829 | 27.0 | 1377 | 1.8670 | 0.6770 | 0.6825 |
80
+ | 0.0839 | 28.0 | 1428 | 1.8763 | 0.6741 | 0.6800 |
81
+ | 0.0839 | 29.0 | 1479 | 1.8925 | 0.6702 | 0.6769 |
82
+ | 0.0802 | 30.0 | 1530 | 1.8968 | 0.6654 | 0.6723 |
83
+
84
+
85
+ ### Framework versions
86
+
87
+ - Transformers 4.26.1
88
+ - Pytorch 1.13.1+cu116
89
+ - Datasets 2.10.0
90
+ - Tokenizers 0.13.2