Hugging Face's logo

DD0101
/
disfluency_base_augmented_90_90

Token Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
1
DD0101 commited on
Commit
22c7e79
•
1 Parent(s): 8d8ff95

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +61 -25
README.md CHANGED
@@ -1,4 +1,5 @@
1
  ---
 
2
  tags:
3
  - generated_from_trainer
4
  metrics:
@@ -16,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  # disfluency-large-3
18
 
19
- This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
- - Loss: 0.0364
22
- - Precision: 0.9849
23
- - Recall: 0.9802
24
- - F1: 0.9825
25
- - Accuracy: 0.9936
26
 
27
  ## Model description
28
 
@@ -51,28 +52,63 @@ The following hyperparameters were used during training:
51
 
52
  ### Training results
53
 
54
- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
55
- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
56
- | No log | 1.0 | 140 | 0.0713 | 0.8955 | 0.9165 | 0.9059 | 0.9816 |
57
- | No log | 2.0 | 280 | 0.0334 | 0.9706 | 0.9730 | 0.9718 | 0.9925 |
58
- | No log | 3.0 | 420 | 0.0584 | 0.9656 | 0.9609 | 0.9633 | 0.9880 |
59
- | 0.1335 | 4.0 | 560 | 0.0352 | 0.9742 | 0.9742 | 0.9742 | 0.9922 |
60
- | 0.1335 | 5.0 | 700 | 0.0539 | 0.9651 | 0.9633 | 0.9642 | 0.9894 |
61
- | 0.1335 | 6.0 | 840 | 0.0293 | 0.9730 | 0.9754 | 0.9742 | 0.9924 |
62
- | 0.1335 | 7.0 | 980 | 0.0364 | 0.9849 | 0.9802 | 0.9825 | 0.9936 |
63
- | 0.0146 | 8.0 | 1120 | 0.0343 | 0.9795 | 0.9778 | 0.9786 | 0.9941 |
64
- | 0.0146 | 9.0 | 1260 | 0.0268 | 0.9802 | 0.9814 | 0.9808 | 0.9947 |
65
- | 0.0146 | 10.0 | 1400 | 0.0427 | 0.9682 | 0.9688 | 0.9685 | 0.9918 |
66
- | 0.0076 | 11.0 | 1540 | 0.0429 | 0.9576 | 0.9633 | 0.9605 | 0.9899 |
67
- | 0.0076 | 12.0 | 1680 | 0.0343 | 0.9735 | 0.9730 | 0.9732 | 0.9933 |
68
- | 0.0076 | 13.0 | 1820 | 0.0305 | 0.9801 | 0.9754 | 0.9777 | 0.9939 |
69
- | 0.0076 | 14.0 | 1960 | 0.0437 | 0.9765 | 0.9742 | 0.9753 | 0.9924 |
70
- | 0.0047 | 15.0 | 2100 | 0.0363 | 0.9778 | 0.9778 | 0.9778 | 0.9939 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
71
 
72
 
73
  ### Framework versions
74
 
75
- - Transformers 4.29.2
76
  - Pytorch 2.0.1+cu118
77
- - Datasets 2.12.0
78
  - Tokenizers 0.13.3
 
1
  ---
2
+ base_model: vinai/phobert-base
3
  tags:
4
  - generated_from_trainer
5
  metrics:
 
17
 
18
  # disfluency-large-3
19
 
20
+ This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.0403
23
+ - Precision: 0.9904
24
+ - Recall: 0.9880
25
+ - F1: 0.9892
26
+ - Accuracy: 0.9962
27
 
28
  ## Model description
29
 
 
52
 
53
  ### Training results
54
 
55
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
56
+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
57
+ | No log | 1.0 | 280 | 0.0331 | 0.9719 | 0.9754 | 0.9736 | 0.9926 |
58
+ | 0.0853 | 2.0 | 560 | 0.0354 | 0.9771 | 0.9736 | 0.9753 | 0.9923 |
59
+ | 0.0853 | 3.0 | 840 | 0.0360 | 0.9759 | 0.9754 | 0.9757 | 0.9928 |
60
+ | 0.0119 | 4.0 | 1120 | 0.0255 | 0.9850 | 0.9838 | 0.9844 | 0.9948 |
61
+ | 0.0119 | 5.0 | 1400 | 0.0300 | 0.9873 | 0.9850 | 0.9862 | 0.9952 |
62
+ | 0.0063 | 6.0 | 1680 | 0.0412 | 0.9848 | 0.9742 | 0.9795 | 0.9927 |
63
+ | 0.0063 | 7.0 | 1960 | 0.0304 | 0.9844 | 0.9838 | 0.9841 | 0.9952 |
64
+ | 0.0039 | 8.0 | 2240 | 0.0344 | 0.9855 | 0.9820 | 0.9837 | 0.9939 |
65
+ | 0.004 | 9.0 | 2520 | 0.0522 | 0.9740 | 0.9681 | 0.9711 | 0.9911 |
66
+ | 0.004 | 10.0 | 2800 | 0.0305 | 0.9790 | 0.9790 | 0.9790 | 0.9943 |
67
+ | 0.0022 | 11.0 | 3080 | 0.0355 | 0.9837 | 0.9820 | 0.9829 | 0.9945 |
68
+ | 0.0022 | 12.0 | 3360 | 0.0400 | 0.9795 | 0.9772 | 0.9783 | 0.9935 |
69
+ | 0.002 | 13.0 | 3640 | 0.0394 | 0.9826 | 0.9814 | 0.9820 | 0.9943 |
70
+ | 0.002 | 14.0 | 3920 | 0.0452 | 0.9795 | 0.9772 | 0.9783 | 0.9930 |
71
+ | 0.0015 | 15.0 | 4200 | 0.0405 | 0.9825 | 0.9808 | 0.9817 | 0.9935 |
72
+ | 0.0015 | 16.0 | 4480 | 0.0373 | 0.9832 | 0.9826 | 0.9829 | 0.9941 |
73
+ | 0.0013 | 17.0 | 4760 | 0.0361 | 0.9832 | 0.9850 | 0.9841 | 0.9946 |
74
+ | 0.0013 | 18.0 | 5040 | 0.0447 | 0.9807 | 0.9790 | 0.9798 | 0.9937 |
75
+ | 0.0013 | 19.0 | 5320 | 0.0340 | 0.9874 | 0.9856 | 0.9865 | 0.9955 |
76
+ | 0.0009 | 20.0 | 5600 | 0.0374 | 0.9873 | 0.9826 | 0.9849 | 0.9948 |
77
+ | 0.0009 | 21.0 | 5880 | 0.0410 | 0.9843 | 0.9784 | 0.9813 | 0.9943 |
78
+ | 0.0007 | 22.0 | 6160 | 0.0275 | 0.9892 | 0.9862 | 0.9877 | 0.9961 |
79
+ | 0.0007 | 23.0 | 6440 | 0.0360 | 0.9891 | 0.9850 | 0.9871 | 0.9960 |
80
+ | 0.0011 | 24.0 | 6720 | 0.0323 | 0.9868 | 0.9850 | 0.9859 | 0.9954 |
81
+ | 0.0006 | 25.0 | 7000 | 0.0386 | 0.9867 | 0.9820 | 0.9843 | 0.9949 |
82
+ | 0.0006 | 26.0 | 7280 | 0.0408 | 0.9819 | 0.9802 | 0.9811 | 0.9940 |
83
+ | 0.0005 | 27.0 | 7560 | 0.0357 | 0.9867 | 0.9826 | 0.9846 | 0.9953 |
84
+ | 0.0005 | 28.0 | 7840 | 0.0370 | 0.9843 | 0.9820 | 0.9832 | 0.9946 |
85
+ | 0.0004 | 29.0 | 8120 | 0.0313 | 0.9880 | 0.9874 | 0.9877 | 0.9960 |
86
+ | 0.0004 | 30.0 | 8400 | 0.0363 | 0.9892 | 0.9862 | 0.9877 | 0.9956 |
87
+ | 0.0004 | 31.0 | 8680 | 0.0402 | 0.9843 | 0.9826 | 0.9835 | 0.9946 |
88
+ | 0.0004 | 32.0 | 8960 | 0.0321 | 0.9868 | 0.9850 | 0.9859 | 0.9956 |
89
+ | 0.0004 | 33.0 | 9240 | 0.0362 | 0.9861 | 0.9838 | 0.9850 | 0.9950 |
90
+ | 0.0003 | 34.0 | 9520 | 0.0307 | 0.9886 | 0.9880 | 0.9883 | 0.9964 |
91
+ | 0.0003 | 35.0 | 9800 | 0.0350 | 0.9880 | 0.9862 | 0.9871 | 0.9956 |
92
+ | 0.0001 | 36.0 | 10080 | 0.0343 | 0.9868 | 0.9856 | 0.9862 | 0.9956 |
93
+ | 0.0001 | 37.0 | 10360 | 0.0374 | 0.9874 | 0.9856 | 0.9865 | 0.9952 |
94
+ | 0.0003 | 38.0 | 10640 | 0.0333 | 0.9874 | 0.9868 | 0.9871 | 0.9957 |
95
+ | 0.0003 | 39.0 | 10920 | 0.0331 | 0.9886 | 0.9862 | 0.9874 | 0.9956 |
96
+ | 0.0001 | 40.0 | 11200 | 0.0349 | 0.9880 | 0.9868 | 0.9874 | 0.9961 |
97
+ | 0.0001 | 41.0 | 11480 | 0.0407 | 0.9880 | 0.9868 | 0.9874 | 0.9958 |
98
+ | 0.0001 | 42.0 | 11760 | 0.0389 | 0.9874 | 0.9868 | 0.9871 | 0.9959 |
99
+ | 0.0001 | 43.0 | 12040 | 0.0387 | 0.9892 | 0.9874 | 0.9883 | 0.9961 |
100
+ | 0.0001 | 44.0 | 12320 | 0.0414 | 0.9886 | 0.9868 | 0.9877 | 0.9959 |
101
+ | 0.0001 | 45.0 | 12600 | 0.0386 | 0.9886 | 0.9868 | 0.9877 | 0.9961 |
102
+ | 0.0001 | 46.0 | 12880 | 0.0408 | 0.9892 | 0.9874 | 0.9883 | 0.9961 |
103
+ | 0.0 | 47.0 | 13160 | 0.0402 | 0.9898 | 0.9880 | 0.9889 | 0.9962 |
104
+ | 0.0 | 48.0 | 13440 | 0.0411 | 0.9886 | 0.9868 | 0.9877 | 0.9959 |
105
+ | 0.0 | 49.0 | 13720 | 0.0403 | 0.9904 | 0.9880 | 0.9892 | 0.9962 |
106
+ | 0.0 | 50.0 | 14000 | 0.0402 | 0.9904 | 0.9880 | 0.9892 | 0.9962 |
107
 
108
 
109
  ### Framework versions
110
 
111
+ - Transformers 4.31.0
112
  - Pytorch 2.0.1+cu118
113
+ - Datasets 2.14.1
114
  - Tokenizers 0.13.3