Hugging Face's logo

salbatarni
/
arabert_cross_organization_task3_fold0

TensorBoard
Safetensors
bert
Generated from Trainer
Model card Files Metrics Community
salbatarni commited on
Commit
dc6f6ee
·
verified ·
1 Parent(s): 12f6ed0

End of training

Browse files
Files changed (1) hide show
  1. README.md +85 -85
README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
- - name: arabert_cross_organization_task2_fold6
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
- # arabert_cross_organization_task2_fold6
14
 
15
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 0.8091
18
- - Qwk: 0.4688
19
- - Mse: 0.8081
20
 
21
  ## Model description
22
 
@@ -47,86 +47,86 @@ The following hyperparameters were used during training:
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.125 | 2 | 2.7795 | 0.0105 | 2.7827 |
51
- | No log | 0.25 | 4 | 1.5291 | 0.1173 | 1.5287 |
52
- | No log | 0.375 | 6 | 0.8451 | 0.3969 | 0.8442 |
53
- | No log | 0.5 | 8 | 0.7864 | 0.4495 | 0.7852 |
54
- | No log | 0.625 | 10 | 0.6936 | 0.4833 | 0.6924 |
55
- | No log | 0.75 | 12 | 1.1360 | 0.3318 | 1.1343 |
56
- | No log | 0.875 | 14 | 1.0124 | 0.3651 | 1.0104 |
57
- | No log | 1.0 | 16 | 0.6020 | 0.5728 | 0.6007 |
58
- | No log | 1.125 | 18 | 0.7313 | 0.4817 | 0.7294 |
59
- | No log | 1.25 | 20 | 0.6700 | 0.4955 | 0.6684 |
60
- | No log | 1.375 | 22 | 0.4911 | 0.6467 | 0.4906 |
61
- | No log | 1.5 | 24 | 0.4996 | 0.7310 | 0.4995 |
62
- | No log | 1.625 | 26 | 0.4835 | 0.5735 | 0.4828 |
63
- | No log | 1.75 | 28 | 0.6109 | 0.4913 | 0.6097 |
64
- | No log | 1.875 | 30 | 0.5349 | 0.5702 | 0.5337 |
65
- | No log | 2.0 | 32 | 0.5033 | 0.6710 | 0.5027 |
66
- | No log | 2.125 | 34 | 0.5412 | 0.6126 | 0.5400 |
67
- | No log | 2.25 | 36 | 0.7223 | 0.4624 | 0.7201 |
68
- | No log | 2.375 | 38 | 0.7359 | 0.4653 | 0.7337 |
69
- | No log | 2.5 | 40 | 0.5466 | 0.5891 | 0.5455 |
70
- | No log | 2.625 | 42 | 0.5036 | 0.7135 | 0.5034 |
71
- | No log | 2.75 | 44 | 0.4797 | 0.6820 | 0.4794 |
72
- | No log | 2.875 | 46 | 0.5194 | 0.5891 | 0.5185 |
73
- | No log | 3.0 | 48 | 0.5890 | 0.5385 | 0.5878 |
74
- | No log | 3.125 | 50 | 0.5541 | 0.5617 | 0.5529 |
75
- | No log | 3.25 | 52 | 0.5096 | 0.6247 | 0.5088 |
76
- | No log | 3.375 | 54 | 0.5168 | 0.6305 | 0.5160 |
77
- | No log | 3.5 | 56 | 0.5860 | 0.5436 | 0.5848 |
78
- | No log | 3.625 | 58 | 0.7175 | 0.4990 | 0.7160 |
79
- | No log | 3.75 | 60 | 0.6365 | 0.5253 | 0.6352 |
80
- | No log | 3.875 | 62 | 0.5233 | 0.6176 | 0.5225 |
81
- | No log | 4.0 | 64 | 0.5179 | 0.6032 | 0.5171 |
82
- | No log | 4.125 | 66 | 0.5802 | 0.5490 | 0.5792 |
83
- | No log | 4.25 | 68 | 0.6555 | 0.5187 | 0.6543 |
84
- | No log | 4.375 | 70 | 0.6681 | 0.5214 | 0.6669 |
85
- | No log | 4.5 | 72 | 0.5977 | 0.5522 | 0.5967 |
86
- | No log | 4.625 | 74 | 0.6327 | 0.5265 | 0.6317 |
87
- | No log | 4.75 | 76 | 0.7255 | 0.4790 | 0.7244 |
88
- | No log | 4.875 | 78 | 0.6478 | 0.5237 | 0.6469 |
89
- | No log | 5.0 | 80 | 0.6738 | 0.4846 | 0.6728 |
90
- | No log | 5.125 | 82 | 0.7006 | 0.4808 | 0.6996 |
91
- | No log | 5.25 | 84 | 0.6997 | 0.4980 | 0.6987 |
92
- | No log | 5.375 | 86 | 0.7244 | 0.5042 | 0.7234 |
93
- | No log | 5.5 | 88 | 0.8734 | 0.4504 | 0.8720 |
94
- | No log | 5.625 | 90 | 0.9975 | 0.3988 | 0.9959 |
95
- | No log | 5.75 | 92 | 0.8921 | 0.4437 | 0.8908 |
96
- | No log | 5.875 | 94 | 0.6714 | 0.5075 | 0.6707 |
97
- | No log | 6.0 | 96 | 0.6012 | 0.5740 | 0.6007 |
98
- | No log | 6.125 | 98 | 0.6310 | 0.5373 | 0.6304 |
99
- | No log | 6.25 | 100 | 0.7371 | 0.4660 | 0.7361 |
100
- | No log | 6.375 | 102 | 0.7404 | 0.4660 | 0.7394 |
101
- | No log | 6.5 | 104 | 0.6821 | 0.5187 | 0.6812 |
102
- | No log | 6.625 | 106 | 0.7033 | 0.5011 | 0.7023 |
103
- | No log | 6.75 | 108 | 0.8055 | 0.4525 | 0.8043 |
104
- | No log | 6.875 | 110 | 0.9021 | 0.4325 | 0.9007 |
105
- | No log | 7.0 | 112 | 0.8396 | 0.4487 | 0.8384 |
106
- | No log | 7.125 | 114 | 0.7100 | 0.5011 | 0.7090 |
107
- | No log | 7.25 | 116 | 0.6902 | 0.5001 | 0.6894 |
108
- | No log | 7.375 | 118 | 0.7441 | 0.4773 | 0.7431 |
109
- | No log | 7.5 | 120 | 0.8389 | 0.4453 | 0.8379 |
110
- | No log | 7.625 | 122 | 0.8787 | 0.4279 | 0.8776 |
111
- | No log | 7.75 | 124 | 0.8597 | 0.4412 | 0.8587 |
112
- | No log | 7.875 | 126 | 0.7923 | 0.4723 | 0.7914 |
113
- | No log | 8.0 | 128 | 0.7502 | 0.4956 | 0.7493 |
114
- | No log | 8.125 | 130 | 0.7529 | 0.4956 | 0.7521 |
115
- | No log | 8.25 | 132 | 0.8227 | 0.4737 | 0.8217 |
116
- | No log | 8.375 | 134 | 0.9122 | 0.4331 | 0.9110 |
117
- | No log | 8.5 | 136 | 0.9081 | 0.4331 | 0.9069 |
118
- | No log | 8.625 | 138 | 0.8495 | 0.4547 | 0.8484 |
119
- | No log | 8.75 | 140 | 0.8359 | 0.4581 | 0.8348 |
120
- | No log | 8.875 | 142 | 0.8222 | 0.4649 | 0.8211 |
121
- | No log | 9.0 | 144 | 0.8247 | 0.4649 | 0.8237 |
122
- | No log | 9.125 | 146 | 0.8487 | 0.4615 | 0.8476 |
123
- | No log | 9.25 | 148 | 0.8495 | 0.4581 | 0.8485 |
124
- | No log | 9.375 | 150 | 0.8322 | 0.4649 | 0.8311 |
125
- | No log | 9.5 | 152 | 0.8155 | 0.4688 | 0.8145 |
126
- | No log | 9.625 | 154 | 0.7982 | 0.4774 | 0.7972 |
127
- | No log | 9.75 | 156 | 0.7978 | 0.4774 | 0.7968 |
128
- | No log | 9.875 | 158 | 0.8054 | 0.4774 | 0.8044 |
129
- | No log | 10.0 | 160 | 0.8091 | 0.4688 | 0.8081 |
130
 
131
 
132
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task3_fold0
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # arabert_cross_organization_task3_fold0
14
 
15
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.6414
18
+ - Qwk: 0.6254
19
+ - Mse: 0.6411
20
 
21
  ## Model description
22
 
 
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
50
+ | No log | 0.125 | 2 | 3.6434 | 0.0780 | 3.6404 |
51
+ | No log | 0.25 | 4 | 1.6551 | 0.1755 | 1.6543 |
52
+ | No log | 0.375 | 6 | 0.9488 | 0.4106 | 0.9484 |
53
+ | No log | 0.5 | 8 | 1.0719 | 0.3366 | 1.0716 |
54
+ | No log | 0.625 | 10 | 1.0207 | 0.3808 | 1.0205 |
55
+ | No log | 0.75 | 12 | 1.0654 | 0.3920 | 1.0651 |
56
+ | No log | 0.875 | 14 | 1.0180 | 0.4457 | 1.0177 |
57
+ | No log | 1.0 | 16 | 0.8222 | 0.5205 | 0.8220 |
58
+ | No log | 1.125 | 18 | 0.7688 | 0.5547 | 0.7686 |
59
+ | No log | 1.25 | 20 | 0.7543 | 0.5667 | 0.7542 |
60
+ | No log | 1.375 | 22 | 0.7022 | 0.5869 | 0.7023 |
61
+ | No log | 1.5 | 24 | 0.6869 | 0.5910 | 0.6872 |
62
+ | No log | 1.625 | 26 | 0.6389 | 0.6198 | 0.6392 |
63
+ | No log | 1.75 | 28 | 0.6739 | 0.6023 | 0.6742 |
64
+ | No log | 1.875 | 30 | 0.8507 | 0.5267 | 0.8506 |
65
+ | No log | 2.0 | 32 | 0.7005 | 0.6030 | 0.7005 |
66
+ | No log | 2.125 | 34 | 0.6617 | 0.6277 | 0.6616 |
67
+ | No log | 2.25 | 36 | 0.6952 | 0.6193 | 0.6949 |
68
+ | No log | 2.375 | 38 | 0.7256 | 0.5870 | 0.7252 |
69
+ | No log | 2.5 | 40 | 0.6299 | 0.6350 | 0.6298 |
70
+ | No log | 2.625 | 42 | 0.6176 | 0.6371 | 0.6175 |
71
+ | No log | 2.75 | 44 | 0.6444 | 0.6384 | 0.6442 |
72
+ | No log | 2.875 | 46 | 0.6872 | 0.5979 | 0.6869 |
73
+ | No log | 3.0 | 48 | 0.8213 | 0.5261 | 0.8207 |
74
+ | No log | 3.125 | 50 | 0.7530 | 0.5473 | 0.7526 |
75
+ | No log | 3.25 | 52 | 0.6049 | 0.6395 | 0.6048 |
76
+ | No log | 3.375 | 54 | 0.6171 | 0.6335 | 0.6172 |
77
+ | No log | 3.5 | 56 | 0.5849 | 0.6419 | 0.5850 |
78
+ | No log | 3.625 | 58 | 0.6694 | 0.5941 | 0.6691 |
79
+ | No log | 3.75 | 60 | 0.7309 | 0.5351 | 0.7304 |
80
+ | No log | 3.875 | 62 | 0.7275 | 0.5529 | 0.7270 |
81
+ | No log | 4.0 | 64 | 0.6510 | 0.5973 | 0.6507 |
82
+ | No log | 4.125 | 66 | 0.6155 | 0.6262 | 0.6153 |
83
+ | No log | 4.25 | 68 | 0.6374 | 0.5996 | 0.6372 |
84
+ | No log | 4.375 | 70 | 0.6653 | 0.5931 | 0.6651 |
85
+ | No log | 4.5 | 72 | 0.6605 | 0.6196 | 0.6604 |
86
+ | No log | 4.625 | 74 | 0.6569 | 0.6417 | 0.6569 |
87
+ | No log | 4.75 | 76 | 0.6686 | 0.6063 | 0.6685 |
88
+ | No log | 4.875 | 78 | 0.7418 | 0.5794 | 0.7412 |
89
+ | No log | 5.0 | 80 | 0.7296 | 0.5729 | 0.7290 |
90
+ | No log | 5.125 | 82 | 0.6713 | 0.6226 | 0.6708 |
91
+ | No log | 5.25 | 84 | 0.6820 | 0.6063 | 0.6815 |
92
+ | No log | 5.375 | 86 | 0.6422 | 0.6148 | 0.6418 |
93
+ | No log | 5.5 | 88 | 0.6309 | 0.6239 | 0.6306 |
94
+ | No log | 5.625 | 90 | 0.6305 | 0.6251 | 0.6303 |
95
+ | No log | 5.75 | 92 | 0.6548 | 0.6222 | 0.6545 |
96
+ | No log | 5.875 | 94 | 0.6437 | 0.6155 | 0.6434 |
97
+ | No log | 6.0 | 96 | 0.6279 | 0.6238 | 0.6276 |
98
+ | No log | 6.125 | 98 | 0.6403 | 0.6193 | 0.6399 |
99
+ | No log | 6.25 | 100 | 0.6589 | 0.6169 | 0.6584 |
100
+ | No log | 6.375 | 102 | 0.6903 | 0.5964 | 0.6897 |
101
+ | No log | 6.5 | 104 | 0.6913 | 0.5965 | 0.6908 |
102
+ | No log | 6.625 | 106 | 0.6504 | 0.6147 | 0.6500 |
103
+ | No log | 6.75 | 108 | 0.6328 | 0.6279 | 0.6326 |
104
+ | No log | 6.875 | 110 | 0.6266 | 0.6408 | 0.6266 |
105
+ | No log | 7.0 | 112 | 0.6369 | 0.6376 | 0.6368 |
106
+ | No log | 7.125 | 114 | 0.6952 | 0.6018 | 0.6949 |
107
+ | No log | 7.25 | 116 | 0.7459 | 0.5938 | 0.7454 |
108
+ | No log | 7.375 | 118 | 0.7167 | 0.5933 | 0.7163 |
109
+ | No log | 7.5 | 120 | 0.6903 | 0.5986 | 0.6900 |
110
+ | No log | 7.625 | 122 | 0.6830 | 0.5957 | 0.6826 |
111
+ | No log | 7.75 | 124 | 0.6864 | 0.6038 | 0.6859 |
112
+ | No log | 7.875 | 126 | 0.6719 | 0.6101 | 0.6715 |
113
+ | No log | 8.0 | 128 | 0.6397 | 0.6237 | 0.6394 |
114
+ | No log | 8.125 | 130 | 0.6323 | 0.6296 | 0.6321 |
115
+ | No log | 8.25 | 132 | 0.6430 | 0.6264 | 0.6428 |
116
+ | No log | 8.375 | 134 | 0.6710 | 0.6229 | 0.6706 |
117
+ | No log | 8.5 | 136 | 0.6705 | 0.6229 | 0.6702 |
118
+ | No log | 8.625 | 138 | 0.6535 | 0.6235 | 0.6533 |
119
+ | No log | 8.75 | 140 | 0.6507 | 0.6235 | 0.6505 |
120
+ | No log | 8.875 | 142 | 0.6514 | 0.6225 | 0.6511 |
121
+ | No log | 9.0 | 144 | 0.6704 | 0.6186 | 0.6700 |
122
+ | No log | 9.125 | 146 | 0.6775 | 0.6242 | 0.6771 |
123
+ | No log | 9.25 | 148 | 0.6775 | 0.6183 | 0.6771 |
124
+ | No log | 9.375 | 150 | 0.6708 | 0.6190 | 0.6704 |
125
+ | No log | 9.5 | 152 | 0.6600 | 0.6231 | 0.6596 |
126
+ | No log | 9.625 | 154 | 0.6487 | 0.6220 | 0.6483 |
127
+ | No log | 9.75 | 156 | 0.6435 | 0.6254 | 0.6432 |
128
+ | No log | 9.875 | 158 | 0.6413 | 0.6266 | 0.6410 |
129
+ | No log | 10.0 | 160 | 0.6414 | 0.6254 | 0.6411 |
130
 
131
 
132
  ### Framework versions