MayBashendy commited on
Commit
c90ed7f
·
verified ·
1 Parent(s): ca66c99

Training in progress, step 300

Browse files
Files changed (4) hide show
  1. README.md +344 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,344 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_run3_AugV5_k20_task2_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_run3_AugV5_k20_task2_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: 1.1495
19
+ - Qwk: 0.1148
20
+ - Mse: 1.1495
21
+ - Rmse: 1.0721
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 | 0.0345 | 2 | 4.4938 | 0.0010 | 4.4938 | 2.1199 |
53
+ | No log | 0.0690 | 4 | 2.5075 | 0.0239 | 2.5075 | 1.5835 |
54
+ | No log | 0.1034 | 6 | 1.9866 | -0.0093 | 1.9866 | 1.4095 |
55
+ | No log | 0.1379 | 8 | 1.5474 | 0.0165 | 1.5474 | 1.2439 |
56
+ | No log | 0.1724 | 10 | 1.3142 | -0.0318 | 1.3142 | 1.1464 |
57
+ | No log | 0.2069 | 12 | 1.4397 | -0.1066 | 1.4397 | 1.1999 |
58
+ | No log | 0.2414 | 14 | 1.4755 | -0.0984 | 1.4755 | 1.2147 |
59
+ | No log | 0.2759 | 16 | 1.2749 | 0.1076 | 1.2749 | 1.1291 |
60
+ | No log | 0.3103 | 18 | 1.2901 | 0.0904 | 1.2901 | 1.1358 |
61
+ | No log | 0.3448 | 20 | 1.2936 | 0.0904 | 1.2936 | 1.1374 |
62
+ | No log | 0.3793 | 22 | 1.3108 | 0.0253 | 1.3108 | 1.1449 |
63
+ | No log | 0.4138 | 24 | 1.5835 | -0.0911 | 1.5835 | 1.2584 |
64
+ | No log | 0.4483 | 26 | 1.7028 | -0.0589 | 1.7028 | 1.3049 |
65
+ | No log | 0.4828 | 28 | 1.7944 | 0.0222 | 1.7944 | 1.3395 |
66
+ | No log | 0.5172 | 30 | 1.9283 | 0.0652 | 1.9283 | 1.3886 |
67
+ | No log | 0.5517 | 32 | 1.6470 | -0.0211 | 1.6470 | 1.2834 |
68
+ | No log | 0.5862 | 34 | 1.4210 | 0.0804 | 1.4210 | 1.1920 |
69
+ | No log | 0.6207 | 36 | 1.7443 | -0.1962 | 1.7443 | 1.3207 |
70
+ | No log | 0.6552 | 38 | 1.5841 | -0.1412 | 1.5841 | 1.2586 |
71
+ | No log | 0.6897 | 40 | 1.3474 | 0.0353 | 1.3474 | 1.1608 |
72
+ | No log | 0.7241 | 42 | 1.3004 | 0.0880 | 1.3004 | 1.1404 |
73
+ | No log | 0.7586 | 44 | 1.2118 | 0.1470 | 1.2118 | 1.1008 |
74
+ | No log | 0.7931 | 46 | 1.2535 | 0.1519 | 1.2535 | 1.1196 |
75
+ | No log | 0.8276 | 48 | 1.2233 | 0.1786 | 1.2233 | 1.1060 |
76
+ | No log | 0.8621 | 50 | 1.3324 | 0.1345 | 1.3324 | 1.1543 |
77
+ | No log | 0.8966 | 52 | 1.3552 | 0.1462 | 1.3552 | 1.1641 |
78
+ | No log | 0.9310 | 54 | 1.4352 | 0.2163 | 1.4352 | 1.1980 |
79
+ | No log | 0.9655 | 56 | 1.2360 | 0.2339 | 1.2360 | 1.1117 |
80
+ | No log | 1.0 | 58 | 1.3379 | 0.2074 | 1.3379 | 1.1567 |
81
+ | No log | 1.0345 | 60 | 1.5697 | 0.1845 | 1.5697 | 1.2529 |
82
+ | No log | 1.0690 | 62 | 1.9875 | 0.1184 | 1.9875 | 1.4098 |
83
+ | No log | 1.1034 | 64 | 1.8836 | 0.1302 | 1.8836 | 1.3724 |
84
+ | No log | 1.1379 | 66 | 1.3730 | 0.2314 | 1.3730 | 1.1718 |
85
+ | No log | 1.1724 | 68 | 1.3854 | 0.2112 | 1.3854 | 1.1770 |
86
+ | No log | 1.2069 | 70 | 1.8657 | 0.1561 | 1.8657 | 1.3659 |
87
+ | No log | 1.2414 | 72 | 2.0294 | 0.0741 | 2.0294 | 1.4246 |
88
+ | No log | 1.2759 | 74 | 1.6428 | 0.2670 | 1.6428 | 1.2817 |
89
+ | No log | 1.3103 | 76 | 1.4436 | 0.2830 | 1.4436 | 1.2015 |
90
+ | No log | 1.3448 | 78 | 1.7119 | 0.1958 | 1.7119 | 1.3084 |
91
+ | No log | 1.3793 | 80 | 2.1057 | 0.0650 | 2.1057 | 1.4511 |
92
+ | No log | 1.4138 | 82 | 1.8519 | 0.1135 | 1.8519 | 1.3608 |
93
+ | No log | 1.4483 | 84 | 1.4165 | 0.2663 | 1.4165 | 1.1902 |
94
+ | No log | 1.4828 | 86 | 1.2317 | 0.2258 | 1.2317 | 1.1098 |
95
+ | No log | 1.5172 | 88 | 1.2763 | 0.2955 | 1.2763 | 1.1297 |
96
+ | No log | 1.5517 | 90 | 1.3216 | 0.3292 | 1.3216 | 1.1496 |
97
+ | No log | 1.5862 | 92 | 1.2066 | 0.2015 | 1.2066 | 1.0985 |
98
+ | No log | 1.6207 | 94 | 1.2134 | 0.1966 | 1.2134 | 1.1016 |
99
+ | No log | 1.6552 | 96 | 1.5064 | 0.3171 | 1.5064 | 1.2274 |
100
+ | No log | 1.6897 | 98 | 1.7677 | 0.1917 | 1.7677 | 1.3295 |
101
+ | No log | 1.7241 | 100 | 1.7285 | 0.1953 | 1.7285 | 1.3147 |
102
+ | No log | 1.7586 | 102 | 1.4052 | 0.2559 | 1.4052 | 1.1854 |
103
+ | No log | 1.7931 | 104 | 1.3271 | 0.25 | 1.3271 | 1.1520 |
104
+ | No log | 1.8276 | 106 | 1.4315 | 0.2679 | 1.4315 | 1.1965 |
105
+ | No log | 1.8621 | 108 | 1.5376 | 0.2418 | 1.5376 | 1.2400 |
106
+ | No log | 1.8966 | 110 | 1.7639 | 0.1484 | 1.7639 | 1.3281 |
107
+ | No log | 1.9310 | 112 | 1.5999 | 0.2685 | 1.5999 | 1.2649 |
108
+ | No log | 1.9655 | 114 | 1.1924 | 0.1737 | 1.1924 | 1.0920 |
109
+ | No log | 2.0 | 116 | 1.1584 | 0.2242 | 1.1584 | 1.0763 |
110
+ | No log | 2.0345 | 118 | 1.2714 | 0.1502 | 1.2714 | 1.1276 |
111
+ | No log | 2.0690 | 120 | 1.4711 | -0.0074 | 1.4711 | 1.2129 |
112
+ | No log | 2.1034 | 122 | 1.4377 | 0.0098 | 1.4377 | 1.1990 |
113
+ | No log | 2.1379 | 124 | 1.2809 | 0.1217 | 1.2809 | 1.1318 |
114
+ | No log | 2.1724 | 126 | 1.1957 | 0.1602 | 1.1957 | 1.0935 |
115
+ | No log | 2.2069 | 128 | 1.3612 | 0.1703 | 1.3612 | 1.1667 |
116
+ | No log | 2.2414 | 130 | 1.5720 | 0.1999 | 1.5720 | 1.2538 |
117
+ | No log | 2.2759 | 132 | 1.4628 | 0.3113 | 1.4628 | 1.2095 |
118
+ | No log | 2.3103 | 134 | 1.3240 | 0.1650 | 1.3240 | 1.1506 |
119
+ | No log | 2.3448 | 136 | 1.3970 | 0.2553 | 1.3970 | 1.1820 |
120
+ | No log | 2.3793 | 138 | 1.4859 | 0.2252 | 1.4859 | 1.2190 |
121
+ | No log | 2.4138 | 140 | 1.3832 | 0.1162 | 1.3832 | 1.1761 |
122
+ | No log | 2.4483 | 142 | 1.2177 | 0.1316 | 1.2177 | 1.1035 |
123
+ | No log | 2.4828 | 144 | 1.1318 | 0.1995 | 1.1318 | 1.0639 |
124
+ | No log | 2.5172 | 146 | 1.1240 | 0.2043 | 1.1240 | 1.0602 |
125
+ | No log | 2.5517 | 148 | 1.1955 | 0.1281 | 1.1955 | 1.0934 |
126
+ | No log | 2.5862 | 150 | 1.4724 | 0.2763 | 1.4724 | 1.2134 |
127
+ | No log | 2.6207 | 152 | 1.5670 | 0.2455 | 1.5670 | 1.2518 |
128
+ | No log | 2.6552 | 154 | 1.3318 | 0.3024 | 1.3318 | 1.1541 |
129
+ | No log | 2.6897 | 156 | 1.1231 | 0.2024 | 1.1231 | 1.0597 |
130
+ | No log | 2.7241 | 158 | 1.1600 | 0.1405 | 1.1600 | 1.0771 |
131
+ | No log | 2.7586 | 160 | 1.4205 | 0.2553 | 1.4205 | 1.1918 |
132
+ | No log | 2.7931 | 162 | 1.5547 | 0.2341 | 1.5547 | 1.2469 |
133
+ | No log | 2.8276 | 164 | 1.5131 | 0.2071 | 1.5131 | 1.2301 |
134
+ | No log | 2.8621 | 166 | 1.3986 | 0.0778 | 1.3986 | 1.1826 |
135
+ | No log | 2.8966 | 168 | 1.1311 | 0.1442 | 1.1311 | 1.0635 |
136
+ | No log | 2.9310 | 170 | 1.0645 | 0.1886 | 1.0645 | 1.0317 |
137
+ | No log | 2.9655 | 172 | 1.1189 | 0.1344 | 1.1189 | 1.0578 |
138
+ | No log | 3.0 | 174 | 1.2551 | 0.1379 | 1.2551 | 1.1203 |
139
+ | No log | 3.0345 | 176 | 1.3157 | 0.1252 | 1.3157 | 1.1470 |
140
+ | No log | 3.0690 | 178 | 1.3161 | 0.1252 | 1.3161 | 1.1472 |
141
+ | No log | 3.1034 | 180 | 1.3035 | 0.1188 | 1.3035 | 1.1417 |
142
+ | No log | 3.1379 | 182 | 1.4424 | 0.1935 | 1.4424 | 1.2010 |
143
+ | No log | 3.1724 | 184 | 1.4486 | 0.0778 | 1.4486 | 1.2036 |
144
+ | No log | 3.2069 | 186 | 1.4669 | 0.1098 | 1.4669 | 1.2112 |
145
+ | No log | 3.2414 | 188 | 1.5143 | 0.1552 | 1.5143 | 1.2306 |
146
+ | No log | 3.2759 | 190 | 1.3785 | 0.0702 | 1.3785 | 1.1741 |
147
+ | No log | 3.3103 | 192 | 1.1979 | 0.1148 | 1.1979 | 1.0945 |
148
+ | No log | 3.3448 | 194 | 1.1663 | 0.1114 | 1.1663 | 1.0800 |
149
+ | No log | 3.3793 | 196 | 1.2717 | 0.1122 | 1.2717 | 1.1277 |
150
+ | No log | 3.4138 | 198 | 1.4301 | 0.2317 | 1.4301 | 1.1959 |
151
+ | No log | 3.4483 | 200 | 1.4458 | 0.3332 | 1.4458 | 1.2024 |
152
+ | No log | 3.4828 | 202 | 1.2530 | 0.1997 | 1.2530 | 1.1194 |
153
+ | No log | 3.5172 | 204 | 1.0864 | 0.2176 | 1.0864 | 1.0423 |
154
+ | No log | 3.5517 | 206 | 1.0889 | 0.1337 | 1.0889 | 1.0435 |
155
+ | No log | 3.5862 | 208 | 1.1892 | 0.1707 | 1.1892 | 1.0905 |
156
+ | No log | 3.6207 | 210 | 1.1701 | 0.1707 | 1.1701 | 1.0817 |
157
+ | No log | 3.6552 | 212 | 1.2250 | 0.1345 | 1.2250 | 1.1068 |
158
+ | No log | 3.6897 | 214 | 1.0927 | 0.1541 | 1.0927 | 1.0453 |
159
+ | No log | 3.7241 | 216 | 0.9878 | 0.2188 | 0.9878 | 0.9939 |
160
+ | No log | 3.7586 | 218 | 1.0501 | 0.1379 | 1.0501 | 1.0248 |
161
+ | No log | 3.7931 | 220 | 1.2811 | 0.0887 | 1.2811 | 1.1318 |
162
+ | No log | 3.8276 | 222 | 1.3902 | 0.0702 | 1.3902 | 1.1791 |
163
+ | No log | 3.8621 | 224 | 1.3513 | 0.0702 | 1.3513 | 1.1625 |
164
+ | No log | 3.8966 | 226 | 1.3778 | 0.0702 | 1.3778 | 1.1738 |
165
+ | No log | 3.9310 | 228 | 1.3797 | 0.0887 | 1.3797 | 1.1746 |
166
+ | No log | 3.9655 | 230 | 1.3473 | 0.0887 | 1.3473 | 1.1607 |
167
+ | No log | 4.0 | 232 | 1.2298 | 0.1479 | 1.2298 | 1.1090 |
168
+ | No log | 4.0345 | 234 | 1.1341 | 0.1541 | 1.1341 | 1.0650 |
169
+ | No log | 4.0690 | 236 | 1.1234 | 0.1541 | 1.1234 | 1.0599 |
170
+ | No log | 4.1034 | 238 | 1.1465 | 0.1479 | 1.1465 | 1.0708 |
171
+ | No log | 4.1379 | 240 | 1.2365 | 0.1477 | 1.2365 | 1.1120 |
172
+ | No log | 4.1724 | 242 | 1.1996 | 0.1637 | 1.1996 | 1.0953 |
173
+ | No log | 4.2069 | 244 | 1.1054 | 0.1538 | 1.1054 | 1.0514 |
174
+ | No log | 4.2414 | 246 | 1.0487 | 0.2009 | 1.0487 | 1.0241 |
175
+ | No log | 4.2759 | 248 | 1.0532 | 0.25 | 1.0532 | 1.0263 |
176
+ | No log | 4.3103 | 250 | 1.2513 | 0.3005 | 1.2513 | 1.1186 |
177
+ | No log | 4.3448 | 252 | 1.5600 | 0.3173 | 1.5600 | 1.2490 |
178
+ | No log | 4.3793 | 254 | 1.4891 | 0.3302 | 1.4891 | 1.2203 |
179
+ | No log | 4.4138 | 256 | 1.2027 | 0.1536 | 1.2027 | 1.0967 |
180
+ | No log | 4.4483 | 258 | 1.1076 | 0.1076 | 1.1076 | 1.0524 |
181
+ | No log | 4.4828 | 260 | 1.1086 | 0.1479 | 1.1086 | 1.0529 |
182
+ | No log | 4.5172 | 262 | 1.2082 | 0.1479 | 1.2082 | 1.0992 |
183
+ | No log | 4.5517 | 264 | 1.3060 | 0.2184 | 1.3060 | 1.1428 |
184
+ | No log | 4.5862 | 266 | 1.4631 | 0.3449 | 1.4631 | 1.2096 |
185
+ | No log | 4.6207 | 268 | 1.2949 | 0.1896 | 1.2949 | 1.1380 |
186
+ | No log | 4.6552 | 270 | 1.1732 | 0.1479 | 1.1732 | 1.0831 |
187
+ | No log | 4.6897 | 272 | 1.2998 | 0.1053 | 1.2998 | 1.1401 |
188
+ | No log | 4.7241 | 274 | 1.5126 | 0.0702 | 1.5126 | 1.2299 |
189
+ | No log | 4.7586 | 276 | 1.6108 | 0.0112 | 1.6108 | 1.2692 |
190
+ | No log | 4.7931 | 278 | 1.6366 | 0.0280 | 1.6366 | 1.2793 |
191
+ | No log | 4.8276 | 280 | 1.5623 | 0.0280 | 1.5623 | 1.2499 |
192
+ | No log | 4.8621 | 282 | 1.5145 | 0.0702 | 1.5145 | 1.2307 |
193
+ | No log | 4.8966 | 284 | 1.2682 | 0.1053 | 1.2682 | 1.1261 |
194
+ | No log | 4.9310 | 286 | 1.0720 | 0.2692 | 1.0720 | 1.0354 |
195
+ | No log | 4.9655 | 288 | 1.0647 | 0.2792 | 1.0647 | 1.0318 |
196
+ | No log | 5.0 | 290 | 1.2157 | 0.1696 | 1.2157 | 1.1026 |
197
+ | No log | 5.0345 | 292 | 1.6247 | 0.2424 | 1.6247 | 1.2746 |
198
+ | No log | 5.0690 | 294 | 1.8100 | 0.1116 | 1.8100 | 1.3454 |
199
+ | No log | 5.1034 | 296 | 1.7243 | 0.1760 | 1.7243 | 1.3131 |
200
+ | No log | 5.1379 | 298 | 1.5301 | 0.0695 | 1.5301 | 1.2370 |
201
+ | No log | 5.1724 | 300 | 1.4212 | 0.0887 | 1.4212 | 1.1922 |
202
+ | No log | 5.2069 | 302 | 1.2468 | 0.1053 | 1.2468 | 1.1166 |
203
+ | No log | 5.2414 | 304 | 1.1413 | 0.1541 | 1.1413 | 1.0683 |
204
+ | No log | 5.2759 | 306 | 1.1954 | 0.1053 | 1.1954 | 1.0934 |
205
+ | No log | 5.3103 | 308 | 1.4139 | 0.1283 | 1.4139 | 1.1891 |
206
+ | No log | 5.3448 | 310 | 1.6411 | 0.1882 | 1.6411 | 1.2810 |
207
+ | No log | 5.3793 | 312 | 1.7220 | 0.2162 | 1.7220 | 1.3122 |
208
+ | No log | 5.4138 | 314 | 1.6276 | 0.0969 | 1.6276 | 1.2758 |
209
+ | No log | 5.4483 | 316 | 1.4510 | 0.0887 | 1.4510 | 1.2046 |
210
+ | No log | 5.4828 | 318 | 1.2877 | 0.0887 | 1.2877 | 1.1348 |
211
+ | No log | 5.5172 | 320 | 1.1830 | 0.1479 | 1.1830 | 1.0877 |
212
+ | No log | 5.5517 | 322 | 1.2123 | 0.1479 | 1.2123 | 1.1011 |
213
+ | No log | 5.5862 | 324 | 1.4207 | 0.1592 | 1.4207 | 1.1919 |
214
+ | No log | 5.6207 | 326 | 1.5763 | 0.3287 | 1.5763 | 1.2555 |
215
+ | No log | 5.6552 | 328 | 1.7295 | 0.3123 | 1.7295 | 1.3151 |
216
+ | No log | 5.6897 | 330 | 1.7018 | 0.3123 | 1.7018 | 1.3045 |
217
+ | No log | 5.7241 | 332 | 1.5736 | 0.3005 | 1.5736 | 1.2544 |
218
+ | No log | 5.7586 | 334 | 1.5674 | 0.2815 | 1.5674 | 1.2520 |
219
+ | No log | 5.7931 | 336 | 1.4409 | 0.2707 | 1.4409 | 1.2004 |
220
+ | No log | 5.8276 | 338 | 1.2659 | 0.1053 | 1.2659 | 1.1251 |
221
+ | No log | 5.8621 | 340 | 1.1049 | 0.1860 | 1.1049 | 1.0511 |
222
+ | No log | 5.8966 | 342 | 1.1200 | 0.2019 | 1.1200 | 1.0583 |
223
+ | No log | 5.9310 | 344 | 1.3070 | 0.2931 | 1.3070 | 1.1432 |
224
+ | No log | 5.9655 | 346 | 1.6109 | 0.2604 | 1.6109 | 1.2692 |
225
+ | No log | 6.0 | 348 | 1.7523 | 0.1359 | 1.7523 | 1.3237 |
226
+ | No log | 6.0345 | 350 | 1.7321 | 0.0717 | 1.7321 | 1.3161 |
227
+ | No log | 6.0690 | 352 | 1.6069 | 0.1929 | 1.6069 | 1.2676 |
228
+ | No log | 6.1034 | 354 | 1.3246 | 0.2184 | 1.3246 | 1.1509 |
229
+ | No log | 6.1379 | 356 | 1.1726 | 0.1405 | 1.1726 | 1.0829 |
230
+ | No log | 6.1724 | 358 | 1.1659 | 0.1379 | 1.1659 | 1.0798 |
231
+ | No log | 6.2069 | 360 | 1.2158 | 0.1479 | 1.2158 | 1.1026 |
232
+ | No log | 6.2414 | 362 | 1.3231 | 0.0887 | 1.3231 | 1.1502 |
233
+ | No log | 6.2759 | 364 | 1.2500 | 0.1316 | 1.2500 | 1.1180 |
234
+ | No log | 6.3103 | 366 | 1.1214 | 0.1048 | 1.1214 | 1.0589 |
235
+ | No log | 6.3448 | 368 | 0.9920 | 0.2019 | 0.9920 | 0.9960 |
236
+ | No log | 6.3793 | 370 | 0.9475 | 0.2772 | 0.9475 | 0.9734 |
237
+ | No log | 6.4138 | 372 | 1.0409 | 0.2930 | 1.0409 | 1.0202 |
238
+ | No log | 6.4483 | 374 | 1.4238 | 0.4203 | 1.4238 | 1.1932 |
239
+ | No log | 6.4828 | 376 | 1.6157 | 0.2938 | 1.6157 | 1.2711 |
240
+ | No log | 6.5172 | 378 | 1.5234 | 0.3254 | 1.5234 | 1.2342 |
241
+ | No log | 6.5517 | 380 | 1.2733 | 0.1316 | 1.2733 | 1.1284 |
242
+ | No log | 6.5862 | 382 | 1.0319 | 0.1279 | 1.0319 | 1.0158 |
243
+ | No log | 6.6207 | 384 | 0.9492 | 0.2448 | 0.9492 | 0.9742 |
244
+ | No log | 6.6552 | 386 | 0.9944 | 0.2432 | 0.9944 | 0.9972 |
245
+ | No log | 6.6897 | 388 | 1.2233 | 0.2424 | 1.2233 | 1.1060 |
246
+ | No log | 6.7241 | 390 | 1.5479 | 0.3263 | 1.5479 | 1.2441 |
247
+ | No log | 6.7586 | 392 | 1.5949 | 0.3063 | 1.5949 | 1.2629 |
248
+ | No log | 6.7931 | 394 | 1.4640 | 0.1882 | 1.4640 | 1.2100 |
249
+ | No log | 6.8276 | 396 | 1.2679 | 0.1944 | 1.2679 | 1.1260 |
250
+ | No log | 6.8621 | 398 | 1.2341 | 0.0887 | 1.2341 | 1.1109 |
251
+ | No log | 6.8966 | 400 | 1.2200 | 0.0887 | 1.2200 | 1.1046 |
252
+ | No log | 6.9310 | 402 | 1.2598 | 0.0887 | 1.2598 | 1.1224 |
253
+ | No log | 6.9655 | 404 | 1.2257 | 0.1219 | 1.2257 | 1.1071 |
254
+ | No log | 7.0 | 406 | 1.2013 | 0.2037 | 1.2013 | 1.0960 |
255
+ | No log | 7.0345 | 408 | 1.2141 | 0.2553 | 1.2141 | 1.1019 |
256
+ | No log | 7.0690 | 410 | 1.1988 | 0.2494 | 1.1988 | 1.0949 |
257
+ | No log | 7.1034 | 412 | 1.1782 | 0.2494 | 1.1782 | 1.0854 |
258
+ | No log | 7.1379 | 414 | 1.0950 | 0.1961 | 1.0950 | 1.0464 |
259
+ | No log | 7.1724 | 416 | 1.1677 | 0.1596 | 1.1677 | 1.0806 |
260
+ | No log | 7.2069 | 418 | 1.3980 | 0.2173 | 1.3980 | 1.1824 |
261
+ | No log | 7.2414 | 420 | 1.4911 | 0.0619 | 1.4911 | 1.2211 |
262
+ | No log | 7.2759 | 422 | 1.4506 | 0.0702 | 1.4506 | 1.2044 |
263
+ | No log | 7.3103 | 424 | 1.3425 | 0.0541 | 1.3425 | 1.1587 |
264
+ | No log | 7.3448 | 426 | 1.2397 | 0.0980 | 1.2397 | 1.1134 |
265
+ | No log | 7.3793 | 428 | 1.1672 | 0.1148 | 1.1672 | 1.0804 |
266
+ | No log | 7.4138 | 430 | 1.1989 | 0.1148 | 1.1989 | 1.0949 |
267
+ | No log | 7.4483 | 432 | 1.2955 | 0.1440 | 1.2955 | 1.1382 |
268
+ | No log | 7.4828 | 434 | 1.3333 | 0.3299 | 1.3333 | 1.1547 |
269
+ | No log | 7.5172 | 436 | 1.3581 | 0.3777 | 1.3581 | 1.1654 |
270
+ | No log | 7.5517 | 438 | 1.4041 | 0.4205 | 1.4041 | 1.1849 |
271
+ | No log | 7.5862 | 440 | 1.2659 | 0.3551 | 1.2659 | 1.1251 |
272
+ | No log | 7.6207 | 442 | 1.0951 | 0.2535 | 1.0951 | 1.0465 |
273
+ | No log | 7.6552 | 444 | 1.0742 | 0.1541 | 1.0742 | 1.0364 |
274
+ | No log | 7.6897 | 446 | 1.0998 | 0.1479 | 1.0998 | 1.0487 |
275
+ | No log | 7.7241 | 448 | 1.2205 | 0.0887 | 1.2205 | 1.1047 |
276
+ | No log | 7.7586 | 450 | 1.3258 | 0.1283 | 1.3258 | 1.1514 |
277
+ | No log | 7.7931 | 452 | 1.3076 | 0.0702 | 1.3076 | 1.1435 |
278
+ | No log | 7.8276 | 454 | 1.2235 | 0.1316 | 1.2235 | 1.1061 |
279
+ | No log | 7.8621 | 456 | 1.0835 | 0.1961 | 1.0835 | 1.0409 |
280
+ | No log | 7.8966 | 458 | 1.0800 | 0.2552 | 1.0800 | 1.0392 |
281
+ | No log | 7.9310 | 460 | 1.2683 | 0.3551 | 1.2683 | 1.1262 |
282
+ | No log | 7.9655 | 462 | 1.5739 | 0.2970 | 1.5739 | 1.2546 |
283
+ | No log | 8.0 | 464 | 1.5930 | 0.3067 | 1.5930 | 1.2621 |
284
+ | No log | 8.0345 | 466 | 1.4223 | 0.1889 | 1.4223 | 1.1926 |
285
+ | No log | 8.0690 | 468 | 1.2266 | 0.0980 | 1.2266 | 1.1075 |
286
+ | No log | 8.1034 | 470 | 1.1617 | 0.1076 | 1.1617 | 1.0778 |
287
+ | No log | 8.1379 | 472 | 1.1682 | 0.0904 | 1.1682 | 1.0808 |
288
+ | No log | 8.1724 | 474 | 1.1906 | 0.0980 | 1.1906 | 1.0911 |
289
+ | No log | 8.2069 | 476 | 1.2292 | 0.1536 | 1.2292 | 1.1087 |
290
+ | No log | 8.2414 | 478 | 1.2571 | 0.2373 | 1.2571 | 1.1212 |
291
+ | No log | 8.2759 | 480 | 1.2057 | 0.2484 | 1.2057 | 1.0980 |
292
+ | No log | 8.3103 | 482 | 1.0812 | 0.0980 | 1.0812 | 1.0398 |
293
+ | No log | 8.3448 | 484 | 1.0309 | 0.1443 | 1.0309 | 1.0154 |
294
+ | No log | 8.3793 | 486 | 1.0686 | 0.1048 | 1.0686 | 1.0337 |
295
+ | No log | 8.4138 | 488 | 1.1739 | 0.1316 | 1.1739 | 1.0834 |
296
+ | No log | 8.4483 | 490 | 1.2144 | 0.1316 | 1.2144 | 1.1020 |
297
+ | No log | 8.4828 | 492 | 1.2481 | 0.0541 | 1.2481 | 1.1172 |
298
+ | No log | 8.5172 | 494 | 1.2381 | 0.0541 | 1.2381 | 1.1127 |
299
+ | No log | 8.5517 | 496 | 1.1721 | 0.0980 | 1.1721 | 1.0826 |
300
+ | No log | 8.5862 | 498 | 1.1100 | 0.1076 | 1.1100 | 1.0536 |
301
+ | 0.3573 | 8.6207 | 500 | 1.0345 | 0.1605 | 1.0345 | 1.0171 |
302
+ | 0.3573 | 8.6552 | 502 | 0.9990 | 0.1505 | 0.9990 | 0.9995 |
303
+ | 0.3573 | 8.6897 | 504 | 1.0137 | 0.1761 | 1.0137 | 1.0068 |
304
+ | 0.3573 | 8.7241 | 506 | 1.1806 | 0.3348 | 1.1806 | 1.0866 |
305
+ | 0.3573 | 8.7586 | 508 | 1.4992 | 0.3205 | 1.4992 | 1.2244 |
306
+ | 0.3573 | 8.7931 | 510 | 1.6938 | 0.2761 | 1.6938 | 1.3015 |
307
+ | 0.3573 | 8.8276 | 512 | 1.6870 | 0.2408 | 1.6870 | 1.2988 |
308
+ | 0.3573 | 8.8621 | 514 | 1.4968 | 0.3140 | 1.4968 | 1.2234 |
309
+ | 0.3573 | 8.8966 | 516 | 1.2628 | 0.3562 | 1.2628 | 1.1237 |
310
+ | 0.3573 | 8.9310 | 518 | 1.1932 | 0.3093 | 1.1932 | 1.0923 |
311
+ | 0.3573 | 8.9655 | 520 | 1.2080 | 0.2173 | 1.2080 | 1.0991 |
312
+ | 0.3573 | 9.0 | 522 | 1.2797 | 0.1840 | 1.2797 | 1.1312 |
313
+ | 0.3573 | 9.0345 | 524 | 1.2820 | 0.1840 | 1.2820 | 1.1323 |
314
+ | 0.3573 | 9.0690 | 526 | 1.2603 | 0.1840 | 1.2603 | 1.1226 |
315
+ | 0.3573 | 9.1034 | 528 | 1.1819 | 0.1894 | 1.1819 | 1.0871 |
316
+ | 0.3573 | 9.1379 | 530 | 1.1374 | 0.2599 | 1.1374 | 1.0665 |
317
+ | 0.3573 | 9.1724 | 532 | 1.1629 | 0.2956 | 1.1629 | 1.0784 |
318
+ | 0.3573 | 9.2069 | 534 | 1.1982 | 0.2790 | 1.1982 | 1.0946 |
319
+ | 0.3573 | 9.2414 | 536 | 1.2084 | 0.2519 | 1.2084 | 1.0993 |
320
+ | 0.3573 | 9.2759 | 538 | 1.2615 | 0.1477 | 1.2615 | 1.1232 |
321
+ | 0.3573 | 9.3103 | 540 | 1.3178 | 0.0887 | 1.3178 | 1.1479 |
322
+ | 0.3573 | 9.3448 | 542 | 1.3253 | 0.0887 | 1.3253 | 1.1512 |
323
+ | 0.3573 | 9.3793 | 544 | 1.2860 | 0.1283 | 1.2860 | 1.1340 |
324
+ | 0.3573 | 9.4138 | 546 | 1.2048 | 0.1894 | 1.2048 | 1.0976 |
325
+ | 0.3573 | 9.4483 | 548 | 1.2059 | 0.2080 | 1.2059 | 1.0981 |
326
+ | 0.3573 | 9.4828 | 550 | 1.2422 | 0.2586 | 1.2422 | 1.1145 |
327
+ | 0.3573 | 9.5172 | 552 | 1.2119 | 0.2037 | 1.2119 | 1.1009 |
328
+ | 0.3573 | 9.5517 | 554 | 1.1484 | 0.2051 | 1.1484 | 1.0717 |
329
+ | 0.3573 | 9.5862 | 556 | 1.1009 | 0.2463 | 1.1009 | 1.0492 |
330
+ | 0.3573 | 9.6207 | 558 | 1.1137 | 0.2463 | 1.1137 | 1.0553 |
331
+ | 0.3573 | 9.6552 | 560 | 1.1747 | 0.2051 | 1.1747 | 1.0838 |
332
+ | 0.3573 | 9.6897 | 562 | 1.2533 | 0.1477 | 1.2533 | 1.1195 |
333
+ | 0.3573 | 9.7241 | 564 | 1.2677 | 0.0887 | 1.2677 | 1.1259 |
334
+ | 0.3573 | 9.7586 | 566 | 1.2401 | 0.0541 | 1.2401 | 1.1136 |
335
+ | 0.3573 | 9.7931 | 568 | 1.1831 | 0.0980 | 1.1831 | 1.0877 |
336
+ | 0.3573 | 9.8276 | 570 | 1.1495 | 0.1148 | 1.1495 | 1.0721 |
337
+
338
+
339
+ ### Framework versions
340
+
341
+ - Transformers 4.44.2
342
+ - Pytorch 2.4.0+cu118
343
+ - Datasets 2.21.0
344
+ - 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:c89ed4e5bea719dcca04d339f72e5ed6082717ca48ea222e5334b3725e56f5f7
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e1252d3fbb72b21f0e8779855ac03cfc61ef95174eb444b57ba018a1ec9af5ec
3
+ size 5304