MayBashendy commited on
Commit
d80e750
·
verified ·
1 Parent(s): 72a823e

End of training

Browse files
Files changed (4) hide show
  1. README.md +320 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,320 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k14_task1_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_B_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k14_task1_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: 0.9060
19
+ - Qwk: 0.6528
20
+ - Mse: 0.9059
21
+ - Rmse: 0.9518
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 | 0.0294 | 2 | 6.8197 | 0.0308 | 6.8197 | 2.6115 |
53
+ | No log | 0.0588 | 4 | 4.5309 | 0.0945 | 4.5309 | 2.1286 |
54
+ | No log | 0.0882 | 6 | 3.3381 | 0.0226 | 3.3381 | 1.8270 |
55
+ | No log | 0.1176 | 8 | 2.6638 | 0.1325 | 2.6638 | 1.6321 |
56
+ | No log | 0.1471 | 10 | 1.9963 | 0.2047 | 1.9963 | 1.4129 |
57
+ | No log | 0.1765 | 12 | 1.8684 | 0.2202 | 1.8684 | 1.3669 |
58
+ | No log | 0.2059 | 14 | 1.9436 | 0.1682 | 1.9436 | 1.3941 |
59
+ | No log | 0.2353 | 16 | 1.8971 | 0.1905 | 1.8971 | 1.3774 |
60
+ | No log | 0.2647 | 18 | 1.7341 | 0.1714 | 1.7341 | 1.3168 |
61
+ | No log | 0.2941 | 20 | 1.6687 | 0.2075 | 1.6687 | 1.2918 |
62
+ | No log | 0.3235 | 22 | 1.7720 | 0.1698 | 1.7720 | 1.3312 |
63
+ | No log | 0.3529 | 24 | 2.0101 | 0.1167 | 2.0101 | 1.4178 |
64
+ | No log | 0.3824 | 26 | 2.4807 | 0.0709 | 2.4807 | 1.5750 |
65
+ | No log | 0.4118 | 28 | 2.6789 | 0.0135 | 2.6789 | 1.6367 |
66
+ | No log | 0.4412 | 30 | 2.4035 | 0.0833 | 2.4035 | 1.5503 |
67
+ | No log | 0.4706 | 32 | 1.9735 | 0.2137 | 1.9735 | 1.4048 |
68
+ | No log | 0.5 | 34 | 1.7333 | 0.2222 | 1.7333 | 1.3166 |
69
+ | No log | 0.5294 | 36 | 1.6178 | 0.2143 | 1.6178 | 1.2719 |
70
+ | No log | 0.5588 | 38 | 1.6814 | 0.1622 | 1.6814 | 1.2967 |
71
+ | No log | 0.5882 | 40 | 1.8363 | 0.1897 | 1.8363 | 1.3551 |
72
+ | No log | 0.6176 | 42 | 1.7297 | 0.1724 | 1.7297 | 1.3152 |
73
+ | No log | 0.6471 | 44 | 1.6567 | 0.1709 | 1.6567 | 1.2871 |
74
+ | No log | 0.6765 | 46 | 1.6473 | 0.2975 | 1.6473 | 1.2835 |
75
+ | No log | 0.7059 | 48 | 1.6339 | 0.2810 | 1.6339 | 1.2783 |
76
+ | No log | 0.7353 | 50 | 1.4977 | 0.3115 | 1.4977 | 1.2238 |
77
+ | No log | 0.7647 | 52 | 1.4125 | 0.3248 | 1.4125 | 1.1885 |
78
+ | No log | 0.7941 | 54 | 1.3721 | 0.3966 | 1.3721 | 1.1714 |
79
+ | No log | 0.8235 | 56 | 1.3618 | 0.3717 | 1.3618 | 1.1670 |
80
+ | No log | 0.8529 | 58 | 1.3272 | 0.3652 | 1.3272 | 1.1520 |
81
+ | No log | 0.8824 | 60 | 1.3405 | 0.3898 | 1.3405 | 1.1578 |
82
+ | No log | 0.9118 | 62 | 1.3804 | 0.3833 | 1.3804 | 1.1749 |
83
+ | No log | 0.9412 | 64 | 1.2838 | 0.5 | 1.2838 | 1.1331 |
84
+ | No log | 0.9706 | 66 | 1.3054 | 0.512 | 1.3054 | 1.1425 |
85
+ | No log | 1.0 | 68 | 1.4800 | 0.4580 | 1.4800 | 1.2166 |
86
+ | No log | 1.0294 | 70 | 1.5923 | 0.3256 | 1.5923 | 1.2619 |
87
+ | No log | 1.0588 | 72 | 1.2293 | 0.4715 | 1.2293 | 1.1087 |
88
+ | No log | 1.0882 | 74 | 1.2682 | 0.4 | 1.2682 | 1.1261 |
89
+ | No log | 1.1176 | 76 | 1.3300 | 0.4 | 1.3300 | 1.1532 |
90
+ | No log | 1.1471 | 78 | 1.2872 | 0.3793 | 1.2872 | 1.1345 |
91
+ | No log | 1.1765 | 80 | 1.3327 | 0.3802 | 1.3327 | 1.1544 |
92
+ | No log | 1.2059 | 82 | 1.2670 | 0.4098 | 1.2670 | 1.1256 |
93
+ | No log | 1.2353 | 84 | 1.3092 | 0.4444 | 1.3092 | 1.1442 |
94
+ | No log | 1.2647 | 86 | 1.3663 | 0.4030 | 1.3663 | 1.1689 |
95
+ | No log | 1.2941 | 88 | 1.2835 | 0.5333 | 1.2835 | 1.1329 |
96
+ | No log | 1.3235 | 90 | 1.2911 | 0.5522 | 1.2911 | 1.1363 |
97
+ | No log | 1.3529 | 92 | 1.3894 | 0.4060 | 1.3894 | 1.1787 |
98
+ | No log | 1.3824 | 94 | 1.5508 | 0.2581 | 1.5508 | 1.2453 |
99
+ | No log | 1.4118 | 96 | 1.6701 | 0.2833 | 1.6701 | 1.2923 |
100
+ | No log | 1.4412 | 98 | 1.5786 | 0.3559 | 1.5786 | 1.2564 |
101
+ | No log | 1.4706 | 100 | 1.3860 | 0.4444 | 1.3860 | 1.1773 |
102
+ | No log | 1.5 | 102 | 1.3283 | 0.4754 | 1.3283 | 1.1525 |
103
+ | No log | 1.5294 | 104 | 1.3236 | 0.4262 | 1.3236 | 1.1505 |
104
+ | No log | 1.5588 | 106 | 1.2869 | 0.4628 | 1.2869 | 1.1344 |
105
+ | No log | 1.5882 | 108 | 1.2100 | 0.4918 | 1.2100 | 1.1000 |
106
+ | No log | 1.6176 | 110 | 1.3107 | 0.4961 | 1.3107 | 1.1449 |
107
+ | No log | 1.6471 | 112 | 1.4033 | 0.4394 | 1.4033 | 1.1846 |
108
+ | No log | 1.6765 | 114 | 1.2775 | 0.5564 | 1.2775 | 1.1303 |
109
+ | No log | 1.7059 | 116 | 1.0337 | 0.5082 | 1.0337 | 1.0167 |
110
+ | No log | 1.7353 | 118 | 1.1093 | 0.5522 | 1.1093 | 1.0533 |
111
+ | No log | 1.7647 | 120 | 1.3278 | 0.4965 | 1.3278 | 1.1523 |
112
+ | No log | 1.7941 | 122 | 1.0769 | 0.5612 | 1.0769 | 1.0378 |
113
+ | No log | 1.8235 | 124 | 0.8877 | 0.6767 | 0.8877 | 0.9422 |
114
+ | No log | 1.8529 | 126 | 1.0692 | 0.5920 | 1.0692 | 1.0340 |
115
+ | No log | 1.8824 | 128 | 1.1410 | 0.5806 | 1.1410 | 1.0682 |
116
+ | No log | 1.9118 | 130 | 1.0140 | 0.5920 | 1.0140 | 1.0070 |
117
+ | No log | 1.9412 | 132 | 0.8940 | 0.6080 | 0.8940 | 0.9455 |
118
+ | No log | 1.9706 | 134 | 0.9085 | 0.528 | 0.9085 | 0.9531 |
119
+ | No log | 2.0 | 136 | 0.9284 | 0.5645 | 0.9284 | 0.9635 |
120
+ | No log | 2.0294 | 138 | 1.0098 | 0.5902 | 1.0098 | 1.0049 |
121
+ | No log | 2.0588 | 140 | 1.2013 | 0.5645 | 1.2013 | 1.0960 |
122
+ | No log | 2.0882 | 142 | 1.2438 | 0.5191 | 1.2438 | 1.1152 |
123
+ | No log | 2.1176 | 144 | 1.0031 | 0.5926 | 1.0031 | 1.0015 |
124
+ | No log | 2.1471 | 146 | 0.8315 | 0.6466 | 0.8315 | 0.9119 |
125
+ | No log | 2.1765 | 148 | 0.8424 | 0.6567 | 0.8424 | 0.9178 |
126
+ | No log | 2.2059 | 150 | 0.9776 | 0.6107 | 0.9776 | 0.9887 |
127
+ | No log | 2.2353 | 152 | 1.1099 | 0.6015 | 1.1099 | 1.0535 |
128
+ | No log | 2.2647 | 154 | 1.1890 | 0.5758 | 1.1890 | 1.0904 |
129
+ | No log | 2.2941 | 156 | 1.2301 | 0.5113 | 1.2301 | 1.1091 |
130
+ | No log | 2.3235 | 158 | 1.2572 | 0.5113 | 1.2572 | 1.1212 |
131
+ | No log | 2.3529 | 160 | 1.1778 | 0.5846 | 1.1778 | 1.0853 |
132
+ | No log | 2.3824 | 162 | 1.1260 | 0.5802 | 1.1260 | 1.0611 |
133
+ | No log | 2.4118 | 164 | 1.1018 | 0.5758 | 1.1018 | 1.0497 |
134
+ | No log | 2.4412 | 166 | 0.9536 | 0.6176 | 0.9536 | 0.9765 |
135
+ | No log | 2.4706 | 168 | 0.9101 | 0.6176 | 0.9101 | 0.9540 |
136
+ | No log | 2.5 | 170 | 0.9343 | 0.5926 | 0.9343 | 0.9666 |
137
+ | No log | 2.5294 | 172 | 0.9077 | 0.5926 | 0.9077 | 0.9527 |
138
+ | No log | 2.5588 | 174 | 0.9062 | 0.5649 | 0.9062 | 0.9520 |
139
+ | No log | 2.5882 | 176 | 0.9881 | 0.5564 | 0.9881 | 0.9941 |
140
+ | No log | 2.6176 | 178 | 0.9764 | 0.5606 | 0.9764 | 0.9881 |
141
+ | No log | 2.6471 | 180 | 0.8647 | 0.6714 | 0.8647 | 0.9299 |
142
+ | No log | 2.6765 | 182 | 0.8154 | 0.6619 | 0.8154 | 0.9030 |
143
+ | No log | 2.7059 | 184 | 0.8174 | 0.6667 | 0.8174 | 0.9041 |
144
+ | No log | 2.7353 | 186 | 0.8385 | 0.6569 | 0.8385 | 0.9157 |
145
+ | No log | 2.7647 | 188 | 0.8960 | 0.6471 | 0.8960 | 0.9466 |
146
+ | No log | 2.7941 | 190 | 0.9310 | 0.6418 | 0.9310 | 0.9649 |
147
+ | No log | 2.8235 | 192 | 0.9794 | 0.6324 | 0.9794 | 0.9897 |
148
+ | No log | 2.8529 | 194 | 1.0001 | 0.6475 | 1.0001 | 1.0001 |
149
+ | No log | 2.8824 | 196 | 0.9737 | 0.6222 | 0.9737 | 0.9867 |
150
+ | No log | 2.9118 | 198 | 1.1565 | 0.5231 | 1.1565 | 1.0754 |
151
+ | No log | 2.9412 | 200 | 1.2072 | 0.4962 | 1.2072 | 1.0987 |
152
+ | No log | 2.9706 | 202 | 1.0250 | 0.5926 | 1.0250 | 1.0124 |
153
+ | No log | 3.0 | 204 | 0.8340 | 0.7133 | 0.8340 | 0.9133 |
154
+ | No log | 3.0294 | 206 | 0.8557 | 0.6713 | 0.8557 | 0.9250 |
155
+ | No log | 3.0588 | 208 | 0.8265 | 0.7075 | 0.8265 | 0.9091 |
156
+ | No log | 3.0882 | 210 | 0.7823 | 0.7211 | 0.7823 | 0.8845 |
157
+ | No log | 3.1176 | 212 | 0.8634 | 0.5942 | 0.8634 | 0.9292 |
158
+ | No log | 3.1471 | 214 | 0.8797 | 0.5942 | 0.8797 | 0.9379 |
159
+ | No log | 3.1765 | 216 | 0.8857 | 0.6715 | 0.8857 | 0.9411 |
160
+ | No log | 3.2059 | 218 | 0.9167 | 0.6618 | 0.9167 | 0.9574 |
161
+ | No log | 3.2353 | 220 | 0.9117 | 0.6370 | 0.9117 | 0.9548 |
162
+ | No log | 3.2647 | 222 | 0.9196 | 0.6906 | 0.9196 | 0.9589 |
163
+ | No log | 3.2941 | 224 | 0.8875 | 0.7050 | 0.8875 | 0.9421 |
164
+ | No log | 3.3235 | 226 | 0.8208 | 0.7042 | 0.8208 | 0.9060 |
165
+ | No log | 3.3529 | 228 | 0.8010 | 0.7383 | 0.8010 | 0.8950 |
166
+ | No log | 3.3824 | 230 | 0.8593 | 0.7027 | 0.8593 | 0.9270 |
167
+ | No log | 3.4118 | 232 | 1.0218 | 0.6486 | 1.0218 | 1.0108 |
168
+ | No log | 3.4412 | 234 | 0.9886 | 0.6486 | 0.9886 | 0.9943 |
169
+ | No log | 3.4706 | 236 | 0.7902 | 0.7075 | 0.7902 | 0.8889 |
170
+ | No log | 3.5 | 238 | 0.6713 | 0.7467 | 0.6713 | 0.8193 |
171
+ | No log | 3.5294 | 240 | 0.6624 | 0.7550 | 0.6624 | 0.8139 |
172
+ | No log | 3.5588 | 242 | 0.7087 | 0.7483 | 0.7087 | 0.8418 |
173
+ | No log | 3.5882 | 244 | 0.8007 | 0.6853 | 0.8007 | 0.8948 |
174
+ | No log | 3.6176 | 246 | 0.8943 | 0.6761 | 0.8943 | 0.9457 |
175
+ | No log | 3.6471 | 248 | 0.8118 | 0.6853 | 0.8118 | 0.9010 |
176
+ | No log | 3.6765 | 250 | 0.7553 | 0.75 | 0.7553 | 0.8691 |
177
+ | No log | 3.7059 | 252 | 0.7476 | 0.7133 | 0.7476 | 0.8646 |
178
+ | No log | 3.7353 | 254 | 0.7037 | 0.75 | 0.7037 | 0.8388 |
179
+ | No log | 3.7647 | 256 | 0.8283 | 0.6853 | 0.8283 | 0.9101 |
180
+ | No log | 3.7941 | 258 | 1.0482 | 0.6622 | 1.0482 | 1.0238 |
181
+ | No log | 3.8235 | 260 | 1.1976 | 0.5658 | 1.1976 | 1.0944 |
182
+ | No log | 3.8529 | 262 | 1.2006 | 0.5541 | 1.2006 | 1.0957 |
183
+ | No log | 3.8824 | 264 | 0.9711 | 0.625 | 0.9711 | 0.9854 |
184
+ | No log | 3.9118 | 266 | 0.7249 | 0.7222 | 0.7249 | 0.8514 |
185
+ | No log | 3.9412 | 268 | 0.7365 | 0.7083 | 0.7365 | 0.8582 |
186
+ | No log | 3.9706 | 270 | 0.7474 | 0.7034 | 0.7474 | 0.8645 |
187
+ | No log | 4.0 | 272 | 0.6991 | 0.7172 | 0.6991 | 0.8361 |
188
+ | No log | 4.0294 | 274 | 0.7767 | 0.6957 | 0.7767 | 0.8813 |
189
+ | No log | 4.0588 | 276 | 0.8155 | 0.6667 | 0.8155 | 0.9030 |
190
+ | No log | 4.0882 | 278 | 0.7908 | 0.6763 | 0.7908 | 0.8893 |
191
+ | No log | 4.1176 | 280 | 0.7333 | 0.7133 | 0.7333 | 0.8563 |
192
+ | No log | 4.1471 | 282 | 0.7786 | 0.7397 | 0.7786 | 0.8824 |
193
+ | No log | 4.1765 | 284 | 0.8953 | 0.7114 | 0.8953 | 0.9462 |
194
+ | No log | 4.2059 | 286 | 0.8581 | 0.7285 | 0.8581 | 0.9264 |
195
+ | No log | 4.2353 | 288 | 0.7443 | 0.7260 | 0.7443 | 0.8628 |
196
+ | No log | 4.2647 | 290 | 0.7496 | 0.7432 | 0.7496 | 0.8658 |
197
+ | No log | 4.2941 | 292 | 0.8544 | 0.6434 | 0.8544 | 0.9244 |
198
+ | No log | 4.3235 | 294 | 0.8505 | 0.6434 | 0.8505 | 0.9222 |
199
+ | No log | 4.3529 | 296 | 0.7592 | 0.7483 | 0.7592 | 0.8713 |
200
+ | No log | 4.3824 | 298 | 0.7677 | 0.7413 | 0.7677 | 0.8762 |
201
+ | No log | 4.4118 | 300 | 0.8216 | 0.6950 | 0.8216 | 0.9064 |
202
+ | No log | 4.4412 | 302 | 0.8006 | 0.7273 | 0.8006 | 0.8948 |
203
+ | No log | 4.4706 | 304 | 0.7853 | 0.7310 | 0.7853 | 0.8862 |
204
+ | No log | 4.5 | 306 | 0.7679 | 0.7310 | 0.7679 | 0.8763 |
205
+ | No log | 4.5294 | 308 | 0.7760 | 0.6812 | 0.7760 | 0.8809 |
206
+ | No log | 4.5588 | 310 | 0.8112 | 0.6429 | 0.8112 | 0.9007 |
207
+ | No log | 4.5882 | 312 | 0.8282 | 0.6241 | 0.8282 | 0.9100 |
208
+ | No log | 4.6176 | 314 | 0.7554 | 0.6857 | 0.7554 | 0.8691 |
209
+ | No log | 4.6471 | 316 | 0.6677 | 0.7397 | 0.6677 | 0.8171 |
210
+ | No log | 4.6765 | 318 | 0.6540 | 0.7568 | 0.6540 | 0.8087 |
211
+ | No log | 4.7059 | 320 | 0.6592 | 0.7397 | 0.6592 | 0.8119 |
212
+ | No log | 4.7353 | 322 | 0.7132 | 0.7211 | 0.7132 | 0.8445 |
213
+ | No log | 4.7647 | 324 | 0.6742 | 0.7297 | 0.6742 | 0.8211 |
214
+ | No log | 4.7941 | 326 | 0.7556 | 0.6980 | 0.7556 | 0.8693 |
215
+ | No log | 4.8235 | 328 | 0.7860 | 0.6980 | 0.7860 | 0.8866 |
216
+ | No log | 4.8529 | 330 | 0.7459 | 0.6980 | 0.7459 | 0.8637 |
217
+ | No log | 4.8824 | 332 | 0.7437 | 0.7222 | 0.7437 | 0.8624 |
218
+ | No log | 4.9118 | 334 | 0.8359 | 0.6993 | 0.8359 | 0.9143 |
219
+ | No log | 4.9412 | 336 | 0.8533 | 0.6993 | 0.8533 | 0.9238 |
220
+ | No log | 4.9706 | 338 | 0.7572 | 0.7222 | 0.7572 | 0.8702 |
221
+ | No log | 5.0 | 340 | 0.6992 | 0.7383 | 0.6992 | 0.8362 |
222
+ | No log | 5.0294 | 342 | 0.6417 | 0.76 | 0.6417 | 0.8011 |
223
+ | No log | 5.0588 | 344 | 0.6322 | 0.7550 | 0.6322 | 0.7951 |
224
+ | No log | 5.0882 | 346 | 0.7314 | 0.7297 | 0.7314 | 0.8552 |
225
+ | No log | 5.1176 | 348 | 0.9230 | 0.7067 | 0.9230 | 0.9608 |
226
+ | No log | 5.1471 | 350 | 0.9531 | 0.7067 | 0.9531 | 0.9763 |
227
+ | No log | 5.1765 | 352 | 0.8595 | 0.7067 | 0.8595 | 0.9271 |
228
+ | No log | 5.2059 | 354 | 0.7495 | 0.7568 | 0.7495 | 0.8658 |
229
+ | No log | 5.2353 | 356 | 0.6563 | 0.8101 | 0.6563 | 0.8101 |
230
+ | No log | 5.2647 | 358 | 0.6607 | 0.7925 | 0.6607 | 0.8128 |
231
+ | No log | 5.2941 | 360 | 0.6206 | 0.7871 | 0.6206 | 0.7878 |
232
+ | No log | 5.3235 | 362 | 0.6342 | 0.7619 | 0.6342 | 0.7964 |
233
+ | No log | 5.3529 | 364 | 0.7461 | 0.7297 | 0.7461 | 0.8638 |
234
+ | No log | 5.3824 | 366 | 0.8153 | 0.6993 | 0.8153 | 0.9029 |
235
+ | No log | 5.4118 | 368 | 0.8234 | 0.6857 | 0.8234 | 0.9074 |
236
+ | No log | 5.4412 | 370 | 0.7971 | 0.6857 | 0.7971 | 0.8928 |
237
+ | No log | 5.4706 | 372 | 0.7923 | 0.6950 | 0.7923 | 0.8901 |
238
+ | No log | 5.5 | 374 | 0.8254 | 0.6857 | 0.8254 | 0.9085 |
239
+ | No log | 5.5294 | 376 | 0.9049 | 0.6232 | 0.9049 | 0.9513 |
240
+ | No log | 5.5588 | 378 | 1.0041 | 0.5839 | 1.0041 | 1.0021 |
241
+ | No log | 5.5882 | 380 | 0.9948 | 0.5672 | 0.9948 | 0.9974 |
242
+ | No log | 5.6176 | 382 | 0.8244 | 0.6897 | 0.8244 | 0.9080 |
243
+ | No log | 5.6471 | 384 | 0.7394 | 0.6944 | 0.7394 | 0.8599 |
244
+ | No log | 5.6765 | 386 | 0.8404 | 0.6713 | 0.8404 | 0.9168 |
245
+ | No log | 5.7059 | 388 | 0.9074 | 0.6761 | 0.9074 | 0.9526 |
246
+ | No log | 5.7353 | 390 | 0.8588 | 0.6522 | 0.8588 | 0.9267 |
247
+ | No log | 5.7647 | 392 | 0.8666 | 0.6094 | 0.8666 | 0.9309 |
248
+ | No log | 5.7941 | 394 | 0.9749 | 0.6154 | 0.9749 | 0.9874 |
249
+ | No log | 5.8235 | 396 | 1.0793 | 0.5522 | 1.0793 | 1.0389 |
250
+ | No log | 5.8529 | 398 | 1.0684 | 0.4964 | 1.0684 | 1.0336 |
251
+ | No log | 5.8824 | 400 | 0.9618 | 0.5865 | 0.9618 | 0.9807 |
252
+ | No log | 5.9118 | 402 | 0.8725 | 0.6714 | 0.8725 | 0.9341 |
253
+ | No log | 5.9412 | 404 | 0.8775 | 0.6761 | 0.8775 | 0.9368 |
254
+ | No log | 5.9706 | 406 | 0.9317 | 0.6667 | 0.9317 | 0.9652 |
255
+ | No log | 6.0 | 408 | 0.9727 | 0.6324 | 0.9727 | 0.9862 |
256
+ | No log | 6.0294 | 410 | 0.9735 | 0.6260 | 0.9735 | 0.9867 |
257
+ | No log | 6.0588 | 412 | 0.9939 | 0.544 | 0.9939 | 0.9969 |
258
+ | No log | 6.0882 | 414 | 1.0127 | 0.6 | 1.0127 | 1.0063 |
259
+ | No log | 6.1176 | 416 | 1.0716 | 0.5522 | 1.0716 | 1.0352 |
260
+ | No log | 6.1471 | 418 | 1.0259 | 0.5522 | 1.0259 | 1.0129 |
261
+ | No log | 6.1765 | 420 | 0.9080 | 0.6269 | 0.9080 | 0.9529 |
262
+ | No log | 6.2059 | 422 | 0.8445 | 0.6857 | 0.8445 | 0.9190 |
263
+ | No log | 6.2353 | 424 | 0.8171 | 0.7172 | 0.8171 | 0.9039 |
264
+ | No log | 6.2647 | 426 | 0.8139 | 0.6986 | 0.8139 | 0.9022 |
265
+ | No log | 6.2941 | 428 | 0.8260 | 0.7211 | 0.8260 | 0.9088 |
266
+ | No log | 6.3235 | 430 | 0.8731 | 0.6986 | 0.8731 | 0.9344 |
267
+ | No log | 6.3529 | 432 | 0.9828 | 0.6069 | 0.9828 | 0.9914 |
268
+ | No log | 6.3824 | 434 | 1.0061 | 0.5942 | 1.0061 | 1.0030 |
269
+ | No log | 6.4118 | 436 | 0.9684 | 0.6479 | 0.9684 | 0.9841 |
270
+ | No log | 6.4412 | 438 | 0.9477 | 0.6338 | 0.9477 | 0.9735 |
271
+ | No log | 6.4706 | 440 | 0.9395 | 0.6294 | 0.9395 | 0.9693 |
272
+ | No log | 6.5 | 442 | 0.9359 | 0.6621 | 0.9359 | 0.9674 |
273
+ | No log | 6.5294 | 444 | 0.9220 | 0.6438 | 0.9220 | 0.9602 |
274
+ | No log | 6.5588 | 446 | 0.9696 | 0.6345 | 0.9696 | 0.9847 |
275
+ | No log | 6.5882 | 448 | 1.0900 | 0.5857 | 1.0900 | 1.0440 |
276
+ | No log | 6.6176 | 450 | 1.0878 | 0.5693 | 1.0878 | 1.0430 |
277
+ | No log | 6.6471 | 452 | 0.9700 | 0.6222 | 0.9700 | 0.9849 |
278
+ | No log | 6.6765 | 454 | 0.8552 | 0.6866 | 0.8552 | 0.9248 |
279
+ | No log | 6.7059 | 456 | 0.8459 | 0.6963 | 0.8459 | 0.9197 |
280
+ | No log | 6.7353 | 458 | 0.8554 | 0.6818 | 0.8554 | 0.9249 |
281
+ | No log | 6.7647 | 460 | 0.8498 | 0.6963 | 0.8498 | 0.9218 |
282
+ | No log | 6.7941 | 462 | 0.8126 | 0.7429 | 0.8126 | 0.9014 |
283
+ | No log | 6.8235 | 464 | 0.7594 | 0.75 | 0.7594 | 0.8714 |
284
+ | No log | 6.8529 | 466 | 0.7451 | 0.7552 | 0.7451 | 0.8632 |
285
+ | No log | 6.8824 | 468 | 0.7828 | 0.7133 | 0.7828 | 0.8848 |
286
+ | No log | 6.9118 | 470 | 0.8521 | 0.7042 | 0.8521 | 0.9231 |
287
+ | No log | 6.9412 | 472 | 0.8301 | 0.7 | 0.8301 | 0.9111 |
288
+ | No log | 6.9706 | 474 | 0.7767 | 0.7194 | 0.7767 | 0.8813 |
289
+ | No log | 7.0 | 476 | 0.7368 | 0.7083 | 0.7368 | 0.8584 |
290
+ | No log | 7.0294 | 478 | 0.7112 | 0.7432 | 0.7112 | 0.8433 |
291
+ | No log | 7.0588 | 480 | 0.6886 | 0.7432 | 0.6886 | 0.8298 |
292
+ | No log | 7.0882 | 482 | 0.6995 | 0.7534 | 0.6995 | 0.8363 |
293
+ | No log | 7.1176 | 484 | 0.7376 | 0.7413 | 0.7376 | 0.8589 |
294
+ | No log | 7.1471 | 486 | 0.8128 | 0.7092 | 0.8128 | 0.9016 |
295
+ | No log | 7.1765 | 488 | 0.8498 | 0.6912 | 0.8498 | 0.9219 |
296
+ | No log | 7.2059 | 490 | 0.8720 | 0.6912 | 0.8720 | 0.9338 |
297
+ | No log | 7.2353 | 492 | 0.8929 | 0.7101 | 0.8929 | 0.9449 |
298
+ | No log | 7.2647 | 494 | 0.9076 | 0.7101 | 0.9076 | 0.9527 |
299
+ | No log | 7.2941 | 496 | 0.9353 | 0.7 | 0.9353 | 0.9671 |
300
+ | No log | 7.3235 | 498 | 0.9534 | 0.6944 | 0.9534 | 0.9764 |
301
+ | 0.4478 | 7.3529 | 500 | 0.9829 | 0.6667 | 0.9829 | 0.9914 |
302
+ | 0.4478 | 7.3824 | 502 | 0.9875 | 0.6667 | 0.9875 | 0.9937 |
303
+ | 0.4478 | 7.4118 | 504 | 0.9654 | 0.6434 | 0.9654 | 0.9825 |
304
+ | 0.4478 | 7.4412 | 506 | 0.9326 | 0.6944 | 0.9326 | 0.9657 |
305
+ | 0.4478 | 7.4706 | 508 | 0.8734 | 0.7183 | 0.8734 | 0.9345 |
306
+ | 0.4478 | 7.5 | 510 | 0.8374 | 0.7183 | 0.8374 | 0.9151 |
307
+ | 0.4478 | 7.5294 | 512 | 0.8439 | 0.7133 | 0.8439 | 0.9186 |
308
+ | 0.4478 | 7.5588 | 514 | 0.9028 | 0.6383 | 0.9028 | 0.9502 |
309
+ | 0.4478 | 7.5882 | 516 | 1.0412 | 0.5735 | 1.0412 | 1.0204 |
310
+ | 0.4478 | 7.6176 | 518 | 1.0448 | 0.6164 | 1.0448 | 1.0221 |
311
+ | 0.4478 | 7.6471 | 520 | 0.9576 | 0.6622 | 0.9576 | 0.9785 |
312
+ | 0.4478 | 7.6765 | 522 | 0.9060 | 0.6528 | 0.9059 | 0.9518 |
313
+
314
+
315
+ ### Framework versions
316
+
317
+ - Transformers 4.44.2
318
+ - Pytorch 2.4.0+cu118
319
+ - Datasets 2.21.0
320
+ - 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:da8d9ecd1869bc150a93af76a182d55b8afec581023e1373c9cca0d6801c164e
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ff6408bd8a0ba29237879d4c3b60b0d7c9eeebf297eb74462e1ce04c215c6bd9
3
+ size 5368