MayBashendy commited on
Commit
5e73069
·
verified ·
1 Parent(s): 10f53bc

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +314 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,314 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k6_task3_organization
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k6_task3_organization
15
+
16
+ This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 0.7962
19
+ - Qwk: -0.0264
20
+ - Mse: 0.7962
21
+ - Rmse: 0.8923
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 2e-05
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 8
43
+ - seed: 42
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 100
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
51
+ |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:|
52
+ | No log | 0.1333 | 2 | 3.9822 | -0.0082 | 3.9822 | 1.9955 |
53
+ | No log | 0.2667 | 4 | 2.3982 | -0.0136 | 2.3982 | 1.5486 |
54
+ | No log | 0.4 | 6 | 1.6759 | -0.0265 | 1.6759 | 1.2946 |
55
+ | No log | 0.5333 | 8 | 1.2573 | 0.0048 | 1.2573 | 1.1213 |
56
+ | No log | 0.6667 | 10 | 1.2414 | -0.1019 | 1.2414 | 1.1142 |
57
+ | No log | 0.8 | 12 | 0.9690 | 0.0486 | 0.9690 | 0.9844 |
58
+ | No log | 0.9333 | 14 | 1.0968 | -0.0435 | 1.0968 | 1.0473 |
59
+ | No log | 1.0667 | 16 | 1.2110 | -0.0510 | 1.2110 | 1.1005 |
60
+ | No log | 1.2 | 18 | 1.1286 | -0.0766 | 1.1286 | 1.0624 |
61
+ | No log | 1.3333 | 20 | 1.0851 | -0.0744 | 1.0851 | 1.0417 |
62
+ | No log | 1.4667 | 22 | 0.9635 | -0.0977 | 0.9635 | 0.9816 |
63
+ | No log | 1.6 | 24 | 0.8958 | -0.0558 | 0.8958 | 0.9465 |
64
+ | No log | 1.7333 | 26 | 0.9410 | -0.0345 | 0.9410 | 0.9700 |
65
+ | No log | 1.8667 | 28 | 0.9650 | -0.0372 | 0.9650 | 0.9823 |
66
+ | No log | 2.0 | 30 | 1.0229 | -0.0101 | 1.0229 | 1.0114 |
67
+ | No log | 2.1333 | 32 | 0.9743 | 0.0046 | 0.9743 | 0.9871 |
68
+ | No log | 2.2667 | 34 | 0.9268 | 0.0642 | 0.9268 | 0.9627 |
69
+ | No log | 2.4 | 36 | 0.8663 | -0.0790 | 0.8663 | 0.9307 |
70
+ | No log | 2.5333 | 38 | 0.9152 | -0.0474 | 0.9152 | 0.9567 |
71
+ | No log | 2.6667 | 40 | 0.9811 | 0.0431 | 0.9811 | 0.9905 |
72
+ | No log | 2.8 | 42 | 1.0918 | -0.0987 | 1.0918 | 1.0449 |
73
+ | No log | 2.9333 | 44 | 1.2348 | -0.0728 | 1.2348 | 1.1112 |
74
+ | No log | 3.0667 | 46 | 1.1715 | -0.0207 | 1.1715 | 1.0824 |
75
+ | No log | 3.2 | 48 | 1.1677 | -0.0193 | 1.1677 | 1.0806 |
76
+ | No log | 3.3333 | 50 | 1.1670 | -0.0720 | 1.1670 | 1.0803 |
77
+ | No log | 3.4667 | 52 | 1.1063 | -0.0084 | 1.1063 | 1.0518 |
78
+ | No log | 3.6 | 54 | 1.0304 | -0.0345 | 1.0304 | 1.0151 |
79
+ | No log | 3.7333 | 56 | 0.9208 | -0.0143 | 0.9208 | 0.9596 |
80
+ | No log | 3.8667 | 58 | 0.8975 | -0.0008 | 0.8975 | 0.9474 |
81
+ | No log | 4.0 | 60 | 0.9550 | 0.0041 | 0.9550 | 0.9772 |
82
+ | No log | 4.1333 | 62 | 0.9794 | -0.0008 | 0.9794 | 0.9896 |
83
+ | No log | 4.2667 | 64 | 0.8147 | -0.0690 | 0.8147 | 0.9026 |
84
+ | No log | 4.4 | 66 | 0.7602 | -0.0215 | 0.7602 | 0.8719 |
85
+ | No log | 4.5333 | 68 | 0.9159 | -0.0823 | 0.9159 | 0.9570 |
86
+ | No log | 4.6667 | 70 | 1.3295 | -0.1501 | 1.3295 | 1.1530 |
87
+ | No log | 4.8 | 72 | 1.1064 | -0.0518 | 1.1064 | 1.0518 |
88
+ | No log | 4.9333 | 74 | 0.7430 | -0.1223 | 0.7430 | 0.8620 |
89
+ | No log | 5.0667 | 76 | 0.7377 | -0.1223 | 0.7377 | 0.8589 |
90
+ | No log | 5.2 | 78 | 0.9211 | -0.0739 | 0.9211 | 0.9597 |
91
+ | No log | 5.3333 | 80 | 1.1283 | -0.1605 | 1.1283 | 1.0622 |
92
+ | No log | 5.4667 | 82 | 0.9667 | -0.0287 | 0.9667 | 0.9832 |
93
+ | No log | 5.6 | 84 | 0.7773 | -0.0035 | 0.7773 | 0.8817 |
94
+ | No log | 5.7333 | 86 | 0.7678 | -0.0035 | 0.7678 | 0.8762 |
95
+ | No log | 5.8667 | 88 | 0.8020 | -0.0739 | 0.8020 | 0.8955 |
96
+ | No log | 6.0 | 90 | 0.8793 | -0.0309 | 0.8793 | 0.9377 |
97
+ | No log | 6.1333 | 92 | 0.7893 | -0.1230 | 0.7893 | 0.8884 |
98
+ | No log | 6.2667 | 94 | 0.8086 | -0.0662 | 0.8086 | 0.8992 |
99
+ | No log | 6.4 | 96 | 0.8793 | -0.1111 | 0.8793 | 0.9377 |
100
+ | No log | 6.5333 | 98 | 0.9071 | -0.1054 | 0.9071 | 0.9524 |
101
+ | No log | 6.6667 | 100 | 0.9155 | -0.1054 | 0.9155 | 0.9568 |
102
+ | No log | 6.8 | 102 | 0.9604 | -0.1180 | 0.9604 | 0.9800 |
103
+ | No log | 6.9333 | 104 | 1.1805 | -0.0128 | 1.1805 | 1.0865 |
104
+ | No log | 7.0667 | 106 | 1.1357 | -0.0133 | 1.1357 | 1.0657 |
105
+ | No log | 7.2 | 108 | 0.9085 | -0.0790 | 0.9085 | 0.9531 |
106
+ | No log | 7.3333 | 110 | 0.8008 | -0.1172 | 0.8008 | 0.8949 |
107
+ | No log | 7.4667 | 112 | 0.7762 | -0.0118 | 0.7762 | 0.8810 |
108
+ | No log | 7.6 | 114 | 0.7736 | -0.0152 | 0.7736 | 0.8796 |
109
+ | No log | 7.7333 | 116 | 0.7743 | -0.0179 | 0.7743 | 0.8800 |
110
+ | No log | 7.8667 | 118 | 0.7031 | 0.0460 | 0.7031 | 0.8385 |
111
+ | No log | 8.0 | 120 | 0.6984 | 0.0460 | 0.6984 | 0.8357 |
112
+ | No log | 8.1333 | 122 | 0.8000 | 0.0129 | 0.8000 | 0.8944 |
113
+ | No log | 8.2667 | 124 | 0.8723 | 0.0456 | 0.8723 | 0.9340 |
114
+ | No log | 8.4 | 126 | 0.7434 | 0.0964 | 0.7434 | 0.8622 |
115
+ | No log | 8.5333 | 128 | 0.7446 | -0.0065 | 0.7446 | 0.8629 |
116
+ | No log | 8.6667 | 130 | 0.7538 | 0.0436 | 0.7538 | 0.8682 |
117
+ | No log | 8.8 | 132 | 0.8310 | -0.1176 | 0.8310 | 0.9116 |
118
+ | No log | 8.9333 | 134 | 0.8894 | -0.0718 | 0.8894 | 0.9431 |
119
+ | No log | 9.0667 | 136 | 0.8567 | -0.0595 | 0.8567 | 0.9256 |
120
+ | No log | 9.2 | 138 | 0.8524 | -0.0595 | 0.8524 | 0.9232 |
121
+ | No log | 9.3333 | 140 | 0.9656 | -0.1194 | 0.9656 | 0.9826 |
122
+ | No log | 9.4667 | 142 | 1.0920 | 0.0250 | 1.0920 | 1.0450 |
123
+ | No log | 9.6 | 144 | 0.8888 | -0.0743 | 0.8888 | 0.9428 |
124
+ | No log | 9.7333 | 146 | 0.7859 | 0.0436 | 0.7859 | 0.8865 |
125
+ | No log | 9.8667 | 148 | 0.7852 | 0.0436 | 0.7852 | 0.8861 |
126
+ | No log | 10.0 | 150 | 0.9263 | -0.0373 | 0.9263 | 0.9624 |
127
+ | No log | 10.1333 | 152 | 1.0345 | 0.0182 | 1.0345 | 1.0171 |
128
+ | No log | 10.2667 | 154 | 0.8501 | -0.0309 | 0.8501 | 0.9220 |
129
+ | No log | 10.4 | 156 | 0.8057 | 0.0296 | 0.8057 | 0.8976 |
130
+ | No log | 10.5333 | 158 | 0.7595 | -0.0160 | 0.7595 | 0.8715 |
131
+ | No log | 10.6667 | 160 | 0.7662 | 0.0334 | 0.7662 | 0.8753 |
132
+ | No log | 10.8 | 162 | 0.7262 | 0.0964 | 0.7262 | 0.8522 |
133
+ | No log | 10.9333 | 164 | 0.7509 | 0.0436 | 0.7509 | 0.8665 |
134
+ | No log | 11.0667 | 166 | 0.8044 | -0.0532 | 0.8044 | 0.8969 |
135
+ | No log | 11.2 | 168 | 0.9225 | -0.0672 | 0.9225 | 0.9604 |
136
+ | No log | 11.3333 | 170 | 0.9281 | -0.1452 | 0.9281 | 0.9634 |
137
+ | No log | 11.4667 | 172 | 0.8447 | -0.0407 | 0.8447 | 0.9191 |
138
+ | No log | 11.6 | 174 | 0.8440 | -0.0350 | 0.8440 | 0.9187 |
139
+ | No log | 11.7333 | 176 | 0.8134 | -0.0849 | 0.8134 | 0.9019 |
140
+ | No log | 11.8667 | 178 | 0.7769 | -0.0030 | 0.7769 | 0.8814 |
141
+ | No log | 12.0 | 180 | 0.7951 | 0.0964 | 0.7951 | 0.8917 |
142
+ | No log | 12.1333 | 182 | 0.7649 | 0.0964 | 0.7649 | 0.8746 |
143
+ | No log | 12.2667 | 184 | 0.7304 | 0.0964 | 0.7304 | 0.8547 |
144
+ | No log | 12.4 | 186 | 0.7424 | -0.0571 | 0.7424 | 0.8616 |
145
+ | No log | 12.5333 | 188 | 0.7573 | -0.1074 | 0.7573 | 0.8702 |
146
+ | No log | 12.6667 | 190 | 0.7721 | -0.0062 | 0.7721 | 0.8787 |
147
+ | No log | 12.8 | 192 | 0.9108 | -0.1580 | 0.9108 | 0.9544 |
148
+ | No log | 12.9333 | 194 | 0.9987 | -0.1102 | 0.9987 | 0.9993 |
149
+ | No log | 13.0667 | 196 | 0.9369 | -0.2288 | 0.9369 | 0.9679 |
150
+ | No log | 13.2 | 198 | 0.9364 | -0.0314 | 0.9364 | 0.9677 |
151
+ | No log | 13.3333 | 200 | 0.9248 | 0.0209 | 0.9248 | 0.9617 |
152
+ | No log | 13.4667 | 202 | 0.9123 | -0.0150 | 0.9123 | 0.9551 |
153
+ | No log | 13.6 | 204 | 0.8242 | -0.1905 | 0.8242 | 0.9079 |
154
+ | No log | 13.7333 | 206 | 0.8009 | -0.1466 | 0.8009 | 0.8949 |
155
+ | No log | 13.8667 | 208 | 0.8139 | -0.1172 | 0.8139 | 0.9022 |
156
+ | No log | 14.0 | 210 | 0.7848 | -0.1172 | 0.7848 | 0.8859 |
157
+ | No log | 14.1333 | 212 | 0.7626 | -0.0033 | 0.7626 | 0.8733 |
158
+ | No log | 14.2667 | 214 | 0.7521 | -0.0065 | 0.7521 | 0.8672 |
159
+ | No log | 14.4 | 216 | 0.7626 | 0.0033 | 0.7626 | 0.8733 |
160
+ | No log | 14.5333 | 218 | 0.7662 | 0.0033 | 0.7662 | 0.8753 |
161
+ | No log | 14.6667 | 220 | 0.7586 | -0.0032 | 0.7586 | 0.8710 |
162
+ | No log | 14.8 | 222 | 0.7751 | -0.1040 | 0.7751 | 0.8804 |
163
+ | No log | 14.9333 | 224 | 0.8102 | -0.1461 | 0.8102 | 0.9001 |
164
+ | No log | 15.0667 | 226 | 0.8531 | -0.0999 | 0.8531 | 0.9237 |
165
+ | No log | 15.2 | 228 | 0.9634 | -0.0778 | 0.9634 | 0.9815 |
166
+ | No log | 15.3333 | 230 | 0.9544 | 0.0017 | 0.9544 | 0.9769 |
167
+ | No log | 15.4667 | 232 | 0.8246 | 0.0318 | 0.8246 | 0.9081 |
168
+ | No log | 15.6 | 234 | 0.7825 | 0.0 | 0.7825 | 0.8846 |
169
+ | No log | 15.7333 | 236 | 0.7954 | -0.1551 | 0.7954 | 0.8919 |
170
+ | No log | 15.8667 | 238 | 0.8050 | -0.2006 | 0.8050 | 0.8972 |
171
+ | No log | 16.0 | 240 | 0.7867 | 0.0454 | 0.7867 | 0.8870 |
172
+ | No log | 16.1333 | 242 | 0.8012 | -0.0091 | 0.8012 | 0.8951 |
173
+ | No log | 16.2667 | 244 | 0.8034 | -0.0091 | 0.8034 | 0.8963 |
174
+ | No log | 16.4 | 246 | 0.7936 | 0.0454 | 0.7936 | 0.8909 |
175
+ | No log | 16.5333 | 248 | 0.8009 | 0.0 | 0.8009 | 0.8949 |
176
+ | No log | 16.6667 | 250 | 0.8033 | -0.0428 | 0.8033 | 0.8963 |
177
+ | No log | 16.8 | 252 | 0.7770 | -0.0032 | 0.7770 | 0.8815 |
178
+ | No log | 16.9333 | 254 | 0.7884 | -0.1168 | 0.7884 | 0.8879 |
179
+ | No log | 17.0667 | 256 | 0.8189 | -0.0725 | 0.8189 | 0.9049 |
180
+ | No log | 17.2 | 258 | 0.8079 | -0.1172 | 0.8079 | 0.8989 |
181
+ | No log | 17.3333 | 260 | 0.8146 | -0.1026 | 0.8146 | 0.9025 |
182
+ | No log | 17.4667 | 262 | 0.8692 | -0.0837 | 0.8692 | 0.9323 |
183
+ | No log | 17.6 | 264 | 0.8758 | -0.0798 | 0.8758 | 0.9358 |
184
+ | No log | 17.7333 | 266 | 0.8802 | -0.1927 | 0.8802 | 0.9382 |
185
+ | No log | 17.8667 | 268 | 0.9527 | -0.0336 | 0.9527 | 0.9761 |
186
+ | No log | 18.0 | 270 | 0.9596 | 0.0476 | 0.9596 | 0.9796 |
187
+ | No log | 18.1333 | 272 | 0.8799 | -0.0163 | 0.8799 | 0.9380 |
188
+ | No log | 18.2667 | 274 | 0.8802 | -0.1885 | 0.8802 | 0.9382 |
189
+ | No log | 18.4 | 276 | 0.9279 | -0.0492 | 0.9279 | 0.9633 |
190
+ | No log | 18.5333 | 278 | 0.9103 | -0.1301 | 0.9103 | 0.9541 |
191
+ | No log | 18.6667 | 280 | 0.8816 | -0.2576 | 0.8816 | 0.9389 |
192
+ | No log | 18.8 | 282 | 0.9289 | 0.0123 | 0.9289 | 0.9638 |
193
+ | No log | 18.9333 | 284 | 1.0079 | 0.0043 | 1.0079 | 1.0039 |
194
+ | No log | 19.0667 | 286 | 0.9616 | 0.0525 | 0.9616 | 0.9806 |
195
+ | No log | 19.2 | 288 | 0.8988 | -0.0533 | 0.8988 | 0.9480 |
196
+ | No log | 19.3333 | 290 | 0.8906 | -0.2128 | 0.8906 | 0.9437 |
197
+ | No log | 19.4667 | 292 | 0.8747 | -0.1659 | 0.8747 | 0.9353 |
198
+ | No log | 19.6 | 294 | 0.8424 | -0.2036 | 0.8424 | 0.9178 |
199
+ | No log | 19.7333 | 296 | 0.8375 | -0.0690 | 0.8375 | 0.9152 |
200
+ | No log | 19.8667 | 298 | 0.8470 | 0.1097 | 0.8470 | 0.9203 |
201
+ | No log | 20.0 | 300 | 0.7930 | -0.0240 | 0.7930 | 0.8905 |
202
+ | No log | 20.1333 | 302 | 0.7500 | -0.0033 | 0.7500 | 0.8660 |
203
+ | No log | 20.2667 | 304 | 0.7426 | -0.0033 | 0.7426 | 0.8617 |
204
+ | No log | 20.4 | 306 | 0.7512 | -0.0033 | 0.7512 | 0.8667 |
205
+ | No log | 20.5333 | 308 | 0.7759 | -0.1168 | 0.7759 | 0.8808 |
206
+ | No log | 20.6667 | 310 | 0.8414 | 0.0214 | 0.8414 | 0.9173 |
207
+ | No log | 20.8 | 312 | 0.8751 | -0.0274 | 0.8751 | 0.9355 |
208
+ | No log | 20.9333 | 314 | 0.8592 | 0.0214 | 0.8592 | 0.9270 |
209
+ | No log | 21.0667 | 316 | 0.8562 | -0.0228 | 0.8562 | 0.9253 |
210
+ | No log | 21.2 | 318 | 0.8933 | -0.0274 | 0.8933 | 0.9451 |
211
+ | No log | 21.3333 | 320 | 0.8955 | 0.0159 | 0.8955 | 0.9463 |
212
+ | No log | 21.4667 | 322 | 0.8460 | -0.0228 | 0.8460 | 0.9198 |
213
+ | No log | 21.6 | 324 | 0.8300 | -0.2051 | 0.8300 | 0.9110 |
214
+ | No log | 21.7333 | 326 | 0.8514 | -0.1397 | 0.8514 | 0.9227 |
215
+ | No log | 21.8667 | 328 | 0.8604 | -0.2257 | 0.8604 | 0.9276 |
216
+ | No log | 22.0 | 330 | 0.8685 | -0.0690 | 0.8685 | 0.9319 |
217
+ | No log | 22.1333 | 332 | 0.8871 | 0.0214 | 0.8871 | 0.9419 |
218
+ | No log | 22.2667 | 334 | 0.8607 | -0.0228 | 0.8607 | 0.9277 |
219
+ | No log | 22.4 | 336 | 0.8194 | -0.1172 | 0.8194 | 0.9052 |
220
+ | No log | 22.5333 | 338 | 0.7865 | 0.0479 | 0.7865 | 0.8869 |
221
+ | No log | 22.6667 | 340 | 0.7770 | -0.0152 | 0.7770 | 0.8815 |
222
+ | No log | 22.8 | 342 | 0.7883 | -0.0240 | 0.7883 | 0.8879 |
223
+ | No log | 22.9333 | 344 | 0.8077 | -0.0240 | 0.8077 | 0.8987 |
224
+ | No log | 23.0667 | 346 | 0.8569 | 0.0628 | 0.8569 | 0.9257 |
225
+ | No log | 23.2 | 348 | 0.8485 | -0.0228 | 0.8485 | 0.9211 |
226
+ | No log | 23.3333 | 350 | 0.8231 | -0.0690 | 0.8231 | 0.9072 |
227
+ | No log | 23.4667 | 352 | 0.8143 | -0.0690 | 0.8143 | 0.9024 |
228
+ | No log | 23.6 | 354 | 0.8076 | -0.0690 | 0.8076 | 0.8986 |
229
+ | No log | 23.7333 | 356 | 0.8100 | -0.0228 | 0.8100 | 0.9000 |
230
+ | No log | 23.8667 | 358 | 0.8000 | -0.0240 | 0.8000 | 0.8944 |
231
+ | No log | 24.0 | 360 | 0.7681 | -0.0675 | 0.7681 | 0.8764 |
232
+ | No log | 24.1333 | 362 | 0.7701 | 0.0496 | 0.7701 | 0.8775 |
233
+ | No log | 24.2667 | 364 | 0.7752 | 0.0496 | 0.7752 | 0.8805 |
234
+ | No log | 24.4 | 366 | 0.7751 | 0.0375 | 0.7751 | 0.8804 |
235
+ | No log | 24.5333 | 368 | 0.7837 | 0.0318 | 0.7837 | 0.8853 |
236
+ | No log | 24.6667 | 370 | 0.7861 | 0.0318 | 0.7861 | 0.8866 |
237
+ | No log | 24.8 | 372 | 0.7892 | -0.0690 | 0.7892 | 0.8884 |
238
+ | No log | 24.9333 | 374 | 0.8015 | -0.0690 | 0.8015 | 0.8952 |
239
+ | No log | 25.0667 | 376 | 0.8053 | -0.0152 | 0.8053 | 0.8974 |
240
+ | No log | 25.2 | 378 | 0.8344 | -0.0690 | 0.8344 | 0.9134 |
241
+ | No log | 25.3333 | 380 | 0.8563 | -0.0690 | 0.8563 | 0.9254 |
242
+ | No log | 25.4667 | 382 | 0.8798 | -0.0704 | 0.8798 | 0.9380 |
243
+ | No log | 25.6 | 384 | 0.8828 | -0.0718 | 0.8828 | 0.9396 |
244
+ | No log | 25.7333 | 386 | 0.8497 | -0.0152 | 0.8497 | 0.9218 |
245
+ | No log | 25.8667 | 388 | 0.8200 | -0.0152 | 0.8200 | 0.9055 |
246
+ | No log | 26.0 | 390 | 0.8091 | -0.0513 | 0.8091 | 0.8995 |
247
+ | No log | 26.1333 | 392 | 0.7928 | 0.0479 | 0.7928 | 0.8904 |
248
+ | No log | 26.2667 | 394 | 0.7690 | -0.0096 | 0.7690 | 0.8769 |
249
+ | No log | 26.4 | 396 | 0.7964 | -0.0152 | 0.7964 | 0.8924 |
250
+ | No log | 26.5333 | 398 | 0.8759 | 0.0159 | 0.8759 | 0.9359 |
251
+ | No log | 26.6667 | 400 | 0.8685 | 0.0159 | 0.8685 | 0.9319 |
252
+ | No log | 26.8 | 402 | 0.8446 | -0.1116 | 0.8446 | 0.9190 |
253
+ | No log | 26.9333 | 404 | 0.8531 | -0.0524 | 0.8531 | 0.9237 |
254
+ | No log | 27.0667 | 406 | 0.8621 | -0.1054 | 0.8621 | 0.9285 |
255
+ | No log | 27.2 | 408 | 0.8699 | -0.1060 | 0.8699 | 0.9327 |
256
+ | No log | 27.3333 | 410 | 0.8983 | -0.0252 | 0.8983 | 0.9478 |
257
+ | No log | 27.4667 | 412 | 0.9027 | 0.0152 | 0.9027 | 0.9501 |
258
+ | No log | 27.6 | 414 | 0.8656 | -0.0704 | 0.8656 | 0.9304 |
259
+ | No log | 27.7333 | 416 | 0.8291 | -0.1172 | 0.8291 | 0.9106 |
260
+ | No log | 27.8667 | 418 | 0.8166 | -0.0033 | 0.8166 | 0.9037 |
261
+ | No log | 28.0 | 420 | 0.8389 | -0.1397 | 0.8389 | 0.9159 |
262
+ | No log | 28.1333 | 422 | 0.8376 | -0.0958 | 0.8376 | 0.9152 |
263
+ | No log | 28.2667 | 424 | 0.8398 | -0.1176 | 0.8398 | 0.9164 |
264
+ | No log | 28.4 | 426 | 0.8487 | 0.0191 | 0.8487 | 0.9213 |
265
+ | No log | 28.5333 | 428 | 0.8365 | 0.0628 | 0.8365 | 0.9146 |
266
+ | No log | 28.6667 | 430 | 0.7881 | -0.0739 | 0.7881 | 0.8878 |
267
+ | No log | 28.8 | 432 | 0.7482 | 0.0436 | 0.7482 | 0.8650 |
268
+ | No log | 28.9333 | 434 | 0.7542 | 0.0436 | 0.7542 | 0.8684 |
269
+ | No log | 29.0667 | 436 | 0.7882 | -0.0152 | 0.7882 | 0.8878 |
270
+ | No log | 29.2 | 438 | 0.8365 | -0.0704 | 0.8365 | 0.9146 |
271
+ | No log | 29.3333 | 440 | 0.8452 | -0.0704 | 0.8452 | 0.9193 |
272
+ | No log | 29.4667 | 442 | 0.8372 | 0.0318 | 0.8372 | 0.9150 |
273
+ | No log | 29.6 | 444 | 0.8188 | -0.0152 | 0.8188 | 0.9049 |
274
+ | No log | 29.7333 | 446 | 0.7965 | -0.0152 | 0.7965 | 0.8925 |
275
+ | No log | 29.8667 | 448 | 0.7909 | 0.0395 | 0.7909 | 0.8893 |
276
+ | No log | 30.0 | 450 | 0.7863 | 0.0395 | 0.7863 | 0.8867 |
277
+ | No log | 30.1333 | 452 | 0.7850 | 0.0454 | 0.7850 | 0.8860 |
278
+ | No log | 30.2667 | 454 | 0.7866 | 0.0454 | 0.7866 | 0.8869 |
279
+ | No log | 30.4 | 456 | 0.7825 | 0.0454 | 0.7825 | 0.8846 |
280
+ | No log | 30.5333 | 458 | 0.7768 | 0.0454 | 0.7768 | 0.8813 |
281
+ | No log | 30.6667 | 460 | 0.7643 | 0.0454 | 0.7643 | 0.8742 |
282
+ | No log | 30.8 | 462 | 0.7629 | 0.0454 | 0.7629 | 0.8735 |
283
+ | No log | 30.9333 | 464 | 0.7669 | 0.0436 | 0.7669 | 0.8757 |
284
+ | No log | 31.0667 | 466 | 0.7955 | 0.0863 | 0.7955 | 0.8919 |
285
+ | No log | 31.2 | 468 | 0.8111 | 0.0282 | 0.8111 | 0.9006 |
286
+ | No log | 31.3333 | 470 | 0.7885 | 0.0395 | 0.7885 | 0.8880 |
287
+ | No log | 31.4667 | 472 | 0.7819 | 0.0471 | 0.7819 | 0.8843 |
288
+ | No log | 31.6 | 474 | 0.7795 | 0.0471 | 0.7795 | 0.8829 |
289
+ | No log | 31.7333 | 476 | 0.7637 | 0.0454 | 0.7637 | 0.8739 |
290
+ | No log | 31.8667 | 478 | 0.7477 | 0.0436 | 0.7477 | 0.8647 |
291
+ | No log | 32.0 | 480 | 0.7582 | -0.0188 | 0.7582 | 0.8707 |
292
+ | No log | 32.1333 | 482 | 0.7576 | -0.0739 | 0.7576 | 0.8704 |
293
+ | No log | 32.2667 | 484 | 0.7713 | -0.0264 | 0.7713 | 0.8783 |
294
+ | No log | 32.4 | 486 | 0.8003 | -0.0252 | 0.8003 | 0.8946 |
295
+ | No log | 32.5333 | 488 | 0.8108 | -0.0658 | 0.8108 | 0.9004 |
296
+ | No log | 32.6667 | 490 | 0.8116 | -0.1111 | 0.8116 | 0.9009 |
297
+ | No log | 32.8 | 492 | 0.8311 | -0.0195 | 0.8311 | 0.9116 |
298
+ | No log | 32.9333 | 494 | 0.8385 | -0.0252 | 0.8385 | 0.9157 |
299
+ | No log | 33.0667 | 496 | 0.8099 | -0.1111 | 0.8099 | 0.8999 |
300
+ | No log | 33.2 | 498 | 0.7986 | 0.0471 | 0.7986 | 0.8937 |
301
+ | 0.2326 | 33.3333 | 500 | 0.7974 | 0.0471 | 0.7974 | 0.8930 |
302
+ | 0.2326 | 33.4667 | 502 | 0.7969 | -0.0550 | 0.7969 | 0.8927 |
303
+ | 0.2326 | 33.6 | 504 | 0.7902 | -0.0595 | 0.7902 | 0.8889 |
304
+ | 0.2326 | 33.7333 | 506 | 0.7974 | -0.0179 | 0.7974 | 0.8930 |
305
+ | 0.2326 | 33.8667 | 508 | 0.7877 | -0.0179 | 0.7877 | 0.8875 |
306
+ | 0.2326 | 34.0 | 510 | 0.7962 | -0.0264 | 0.7962 | 0.8923 |
307
+
308
+
309
+ ### Framework versions
310
+
311
+ - Transformers 4.44.2
312
+ - Pytorch 2.4.0+cu118
313
+ - Datasets 2.21.0
314
+ - Tokenizers 0.19.1
config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "aubmindlab/bert-base-arabertv02",
3
+ "architectures": [
4
+ "BertForSequenceClassification"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "hidden_act": "gelu",
9
+ "hidden_dropout_prob": 0.1,
10
+ "hidden_size": 768,
11
+ "id2label": {
12
+ "0": "LABEL_0"
13
+ },
14
+ "initializer_range": 0.02,
15
+ "intermediate_size": 3072,
16
+ "label2id": {
17
+ "LABEL_0": 0
18
+ },
19
+ "layer_norm_eps": 1e-12,
20
+ "max_position_embeddings": 512,
21
+ "model_type": "bert",
22
+ "num_attention_heads": 12,
23
+ "num_hidden_layers": 12,
24
+ "pad_token_id": 0,
25
+ "position_embedding_type": "absolute",
26
+ "problem_type": "regression",
27
+ "torch_dtype": "float32",
28
+ "transformers_version": "4.44.2",
29
+ "type_vocab_size": 2,
30
+ "use_cache": true,
31
+ "vocab_size": 64000
32
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:057f1b6ed4e7d6c833cecc5682b060436d4966035a598743e3e71609d544b949
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:afd567430b367a25b36c0cca8b58dd7a5864f79f085b0e2eb24ad02ae15683fa
3
+ size 5304