MayBashendy commited on
Commit
fddf369
·
verified ·
1 Parent(s): 10ea93e

Training in progress, step 500

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_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task5_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_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task5_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: 0.6063
19
+ - Qwk: 0.6348
20
+ - Mse: 0.6063
21
+ - Rmse: 0.7787
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 | 0.025 | 2 | 4.1556 | 0.0035 | 4.1556 | 2.0385 |
53
+ | No log | 0.05 | 4 | 2.2190 | 0.0203 | 2.2190 | 1.4896 |
54
+ | No log | 0.075 | 6 | 1.3883 | -0.0180 | 1.3883 | 1.1783 |
55
+ | No log | 0.1 | 8 | 1.0683 | 0.2711 | 1.0683 | 1.0336 |
56
+ | No log | 0.125 | 10 | 1.0352 | 0.4205 | 1.0352 | 1.0175 |
57
+ | No log | 0.15 | 12 | 1.0448 | 0.2865 | 1.0448 | 1.0221 |
58
+ | No log | 0.175 | 14 | 1.0528 | 0.2161 | 1.0528 | 1.0260 |
59
+ | No log | 0.2 | 16 | 1.0382 | 0.1263 | 1.0382 | 1.0189 |
60
+ | No log | 0.225 | 18 | 1.0084 | 0.2365 | 1.0084 | 1.0042 |
61
+ | No log | 0.25 | 20 | 1.0114 | 0.2416 | 1.0114 | 1.0057 |
62
+ | No log | 0.275 | 22 | 1.0707 | 0.2640 | 1.0707 | 1.0347 |
63
+ | No log | 0.3 | 24 | 1.1175 | 0.3090 | 1.1175 | 1.0571 |
64
+ | No log | 0.325 | 26 | 1.0302 | 0.3069 | 1.0302 | 1.0150 |
65
+ | No log | 0.35 | 28 | 0.8929 | 0.3891 | 0.8929 | 0.9449 |
66
+ | No log | 0.375 | 30 | 0.9809 | 0.3860 | 0.9809 | 0.9904 |
67
+ | No log | 0.4 | 32 | 1.0953 | 0.2790 | 1.0953 | 1.0465 |
68
+ | No log | 0.425 | 34 | 0.9048 | 0.3972 | 0.9048 | 0.9512 |
69
+ | No log | 0.45 | 36 | 0.8112 | 0.4557 | 0.8112 | 0.9007 |
70
+ | No log | 0.475 | 38 | 0.9695 | 0.2864 | 0.9695 | 0.9846 |
71
+ | No log | 0.5 | 40 | 1.2148 | 0.3340 | 1.2148 | 1.1022 |
72
+ | No log | 0.525 | 42 | 1.1005 | 0.3296 | 1.1005 | 1.0491 |
73
+ | No log | 0.55 | 44 | 0.7862 | 0.4754 | 0.7862 | 0.8867 |
74
+ | No log | 0.575 | 46 | 0.8583 | 0.4665 | 0.8583 | 0.9264 |
75
+ | No log | 0.6 | 48 | 1.2013 | 0.3388 | 1.2013 | 1.0960 |
76
+ | No log | 0.625 | 50 | 1.3987 | 0.2682 | 1.3987 | 1.1826 |
77
+ | No log | 0.65 | 52 | 1.6462 | 0.2136 | 1.6462 | 1.2831 |
78
+ | No log | 0.675 | 54 | 1.5795 | 0.2923 | 1.5795 | 1.2568 |
79
+ | No log | 0.7 | 56 | 1.3293 | 0.3998 | 1.3293 | 1.1529 |
80
+ | No log | 0.725 | 58 | 1.2785 | 0.2510 | 1.2785 | 1.1307 |
81
+ | No log | 0.75 | 60 | 1.0521 | 0.4307 | 1.0521 | 1.0257 |
82
+ | No log | 0.775 | 62 | 0.8837 | 0.5363 | 0.8837 | 0.9400 |
83
+ | No log | 0.8 | 64 | 0.8636 | 0.5215 | 0.8636 | 0.9293 |
84
+ | No log | 0.825 | 66 | 0.8960 | 0.4983 | 0.8960 | 0.9466 |
85
+ | No log | 0.85 | 68 | 1.0048 | 0.4619 | 1.0048 | 1.0024 |
86
+ | No log | 0.875 | 70 | 1.0707 | 0.4063 | 1.0707 | 1.0347 |
87
+ | No log | 0.9 | 72 | 1.0519 | 0.4389 | 1.0519 | 1.0256 |
88
+ | No log | 0.925 | 74 | 1.0855 | 0.3998 | 1.0855 | 1.0419 |
89
+ | No log | 0.95 | 76 | 0.9323 | 0.4694 | 0.9323 | 0.9656 |
90
+ | No log | 0.975 | 78 | 0.8083 | 0.5032 | 0.8083 | 0.8991 |
91
+ | No log | 1.0 | 80 | 0.7585 | 0.4752 | 0.7585 | 0.8709 |
92
+ | No log | 1.025 | 82 | 0.7828 | 0.4847 | 0.7828 | 0.8847 |
93
+ | No log | 1.05 | 84 | 0.9438 | 0.4474 | 0.9438 | 0.9715 |
94
+ | No log | 1.075 | 86 | 1.1100 | 0.2632 | 1.1100 | 1.0536 |
95
+ | No log | 1.1 | 88 | 1.1058 | 0.3045 | 1.1058 | 1.0516 |
96
+ | No log | 1.125 | 90 | 1.0062 | 0.4130 | 1.0062 | 1.0031 |
97
+ | No log | 1.15 | 92 | 0.7599 | 0.5571 | 0.7599 | 0.8717 |
98
+ | No log | 1.175 | 94 | 0.6930 | 0.5833 | 0.6930 | 0.8324 |
99
+ | No log | 1.2 | 96 | 0.6731 | 0.6342 | 0.6731 | 0.8204 |
100
+ | No log | 1.225 | 98 | 0.7205 | 0.6113 | 0.7205 | 0.8488 |
101
+ | No log | 1.25 | 100 | 0.8902 | 0.5458 | 0.8902 | 0.9435 |
102
+ | No log | 1.275 | 102 | 0.9048 | 0.5222 | 0.9048 | 0.9512 |
103
+ | No log | 1.3 | 104 | 0.8044 | 0.5353 | 0.8044 | 0.8969 |
104
+ | No log | 1.325 | 106 | 0.7411 | 0.5554 | 0.7411 | 0.8609 |
105
+ | No log | 1.35 | 108 | 0.7744 | 0.5342 | 0.7744 | 0.8800 |
106
+ | No log | 1.375 | 110 | 0.9023 | 0.5110 | 0.9023 | 0.9499 |
107
+ | No log | 1.4 | 112 | 1.1121 | 0.4281 | 1.1121 | 1.0546 |
108
+ | No log | 1.425 | 114 | 1.0828 | 0.4295 | 1.0828 | 1.0406 |
109
+ | No log | 1.45 | 116 | 0.9450 | 0.4681 | 0.9450 | 0.9721 |
110
+ | No log | 1.475 | 118 | 0.7647 | 0.5046 | 0.7647 | 0.8745 |
111
+ | No log | 1.5 | 120 | 0.7354 | 0.5413 | 0.7354 | 0.8576 |
112
+ | No log | 1.525 | 122 | 0.8142 | 0.5458 | 0.8142 | 0.9023 |
113
+ | No log | 1.55 | 124 | 0.8284 | 0.5140 | 0.8284 | 0.9102 |
114
+ | No log | 1.575 | 126 | 0.7425 | 0.5728 | 0.7425 | 0.8617 |
115
+ | No log | 1.6 | 128 | 0.6671 | 0.6438 | 0.6671 | 0.8167 |
116
+ | No log | 1.625 | 130 | 0.6290 | 0.6438 | 0.6290 | 0.7931 |
117
+ | No log | 1.65 | 132 | 0.6268 | 0.6806 | 0.6268 | 0.7917 |
118
+ | No log | 1.675 | 134 | 0.6232 | 0.6965 | 0.6232 | 0.7894 |
119
+ | No log | 1.7 | 136 | 0.6015 | 0.6939 | 0.6015 | 0.7756 |
120
+ | No log | 1.725 | 138 | 0.5964 | 0.6921 | 0.5964 | 0.7723 |
121
+ | No log | 1.75 | 140 | 0.5883 | 0.7314 | 0.5883 | 0.7670 |
122
+ | No log | 1.775 | 142 | 0.5833 | 0.6911 | 0.5833 | 0.7638 |
123
+ | No log | 1.8 | 144 | 0.6086 | 0.6675 | 0.6086 | 0.7801 |
124
+ | No log | 1.825 | 146 | 0.5885 | 0.6796 | 0.5885 | 0.7672 |
125
+ | No log | 1.85 | 148 | 0.6142 | 0.6807 | 0.6142 | 0.7837 |
126
+ | No log | 1.875 | 150 | 0.7116 | 0.5266 | 0.7116 | 0.8436 |
127
+ | No log | 1.9 | 152 | 0.7433 | 0.5254 | 0.7433 | 0.8621 |
128
+ | No log | 1.925 | 154 | 0.8058 | 0.5254 | 0.8058 | 0.8977 |
129
+ | No log | 1.95 | 156 | 0.7743 | 0.5370 | 0.7743 | 0.8799 |
130
+ | No log | 1.975 | 158 | 0.7236 | 0.5912 | 0.7236 | 0.8506 |
131
+ | No log | 2.0 | 160 | 0.7078 | 0.5799 | 0.7078 | 0.8413 |
132
+ | No log | 2.025 | 162 | 0.6440 | 0.6035 | 0.6440 | 0.8025 |
133
+ | No log | 2.05 | 164 | 0.6431 | 0.6177 | 0.6431 | 0.8020 |
134
+ | No log | 2.075 | 166 | 0.6840 | 0.5964 | 0.6840 | 0.8270 |
135
+ | No log | 2.1 | 168 | 0.7873 | 0.5220 | 0.7873 | 0.8873 |
136
+ | No log | 2.125 | 170 | 0.9002 | 0.5179 | 0.9002 | 0.9488 |
137
+ | No log | 2.15 | 172 | 0.8117 | 0.5318 | 0.8117 | 0.9009 |
138
+ | No log | 2.175 | 174 | 0.7129 | 0.5651 | 0.7129 | 0.8444 |
139
+ | No log | 2.2 | 176 | 0.6786 | 0.5734 | 0.6786 | 0.8237 |
140
+ | No log | 2.225 | 178 | 0.6649 | 0.5862 | 0.6649 | 0.8154 |
141
+ | No log | 2.25 | 180 | 0.6733 | 0.6276 | 0.6733 | 0.8205 |
142
+ | No log | 2.275 | 182 | 0.6856 | 0.5855 | 0.6856 | 0.8280 |
143
+ | No log | 2.3 | 184 | 0.6852 | 0.6228 | 0.6852 | 0.8278 |
144
+ | No log | 2.325 | 186 | 0.6875 | 0.6228 | 0.6875 | 0.8292 |
145
+ | No log | 2.35 | 188 | 0.6797 | 0.6412 | 0.6797 | 0.8244 |
146
+ | No log | 2.375 | 190 | 0.7055 | 0.6502 | 0.7055 | 0.8399 |
147
+ | No log | 2.4 | 192 | 0.6928 | 0.6352 | 0.6928 | 0.8323 |
148
+ | No log | 2.425 | 194 | 0.7501 | 0.5963 | 0.7501 | 0.8661 |
149
+ | No log | 2.45 | 196 | 0.7779 | 0.5877 | 0.7779 | 0.8820 |
150
+ | No log | 2.475 | 198 | 0.7278 | 0.5697 | 0.7278 | 0.8531 |
151
+ | No log | 2.5 | 200 | 0.6380 | 0.6464 | 0.6380 | 0.7988 |
152
+ | No log | 2.525 | 202 | 0.6311 | 0.6983 | 0.6311 | 0.7944 |
153
+ | No log | 2.55 | 204 | 0.6317 | 0.7054 | 0.6317 | 0.7948 |
154
+ | No log | 2.575 | 206 | 0.6728 | 0.6620 | 0.6728 | 0.8202 |
155
+ | No log | 2.6 | 208 | 0.8481 | 0.5076 | 0.8481 | 0.9209 |
156
+ | No log | 2.625 | 210 | 0.8731 | 0.5 | 0.8731 | 0.9344 |
157
+ | No log | 2.65 | 212 | 0.8129 | 0.4946 | 0.8129 | 0.9016 |
158
+ | No log | 2.675 | 214 | 0.7742 | 0.5183 | 0.7742 | 0.8799 |
159
+ | No log | 2.7 | 216 | 0.7356 | 0.5397 | 0.7356 | 0.8577 |
160
+ | No log | 2.725 | 218 | 0.7008 | 0.6537 | 0.7008 | 0.8371 |
161
+ | No log | 2.75 | 220 | 0.6658 | 0.6628 | 0.6658 | 0.8160 |
162
+ | No log | 2.775 | 222 | 0.6799 | 0.6357 | 0.6799 | 0.8245 |
163
+ | No log | 2.8 | 224 | 0.7482 | 0.5958 | 0.7482 | 0.8650 |
164
+ | No log | 2.825 | 226 | 0.7589 | 0.5451 | 0.7589 | 0.8712 |
165
+ | No log | 2.85 | 228 | 0.7369 | 0.5482 | 0.7369 | 0.8585 |
166
+ | No log | 2.875 | 230 | 0.7064 | 0.4660 | 0.7064 | 0.8405 |
167
+ | No log | 2.9 | 232 | 0.7280 | 0.4547 | 0.7280 | 0.8532 |
168
+ | No log | 2.925 | 234 | 0.7637 | 0.5572 | 0.7637 | 0.8739 |
169
+ | No log | 2.95 | 236 | 0.8807 | 0.5 | 0.8807 | 0.9385 |
170
+ | No log | 2.975 | 238 | 0.8260 | 0.5 | 0.8260 | 0.9088 |
171
+ | No log | 3.0 | 240 | 0.7612 | 0.5602 | 0.7612 | 0.8725 |
172
+ | No log | 3.025 | 242 | 0.7298 | 0.5602 | 0.7298 | 0.8543 |
173
+ | No log | 3.05 | 244 | 0.7097 | 0.6137 | 0.7097 | 0.8424 |
174
+ | No log | 3.075 | 246 | 0.7519 | 0.5658 | 0.7519 | 0.8671 |
175
+ | No log | 3.1 | 248 | 0.8287 | 0.5486 | 0.8287 | 0.9103 |
176
+ | No log | 3.125 | 250 | 0.8533 | 0.5385 | 0.8533 | 0.9238 |
177
+ | No log | 3.15 | 252 | 0.8051 | 0.5425 | 0.8051 | 0.8973 |
178
+ | No log | 3.175 | 254 | 0.7461 | 0.5397 | 0.7461 | 0.8638 |
179
+ | No log | 3.2 | 256 | 0.7864 | 0.5675 | 0.7864 | 0.8868 |
180
+ | No log | 3.225 | 258 | 0.7941 | 0.5675 | 0.7941 | 0.8911 |
181
+ | No log | 3.25 | 260 | 0.8501 | 0.4894 | 0.8501 | 0.9220 |
182
+ | No log | 3.275 | 262 | 0.9373 | 0.4681 | 0.9373 | 0.9682 |
183
+ | No log | 3.3 | 264 | 0.9272 | 0.4503 | 0.9272 | 0.9629 |
184
+ | No log | 3.325 | 266 | 0.7445 | 0.6045 | 0.7445 | 0.8629 |
185
+ | No log | 3.35 | 268 | 0.6724 | 0.6209 | 0.6724 | 0.8200 |
186
+ | No log | 3.375 | 270 | 0.6681 | 0.5905 | 0.6681 | 0.8174 |
187
+ | No log | 3.4 | 272 | 0.6926 | 0.5975 | 0.6926 | 0.8322 |
188
+ | No log | 3.425 | 274 | 0.7322 | 0.5864 | 0.7322 | 0.8557 |
189
+ | No log | 3.45 | 276 | 0.7336 | 0.6045 | 0.7336 | 0.8565 |
190
+ | No log | 3.475 | 278 | 0.7013 | 0.5777 | 0.7013 | 0.8375 |
191
+ | No log | 3.5 | 280 | 0.6560 | 0.5657 | 0.6560 | 0.8099 |
192
+ | No log | 3.525 | 282 | 0.6469 | 0.5631 | 0.6469 | 0.8043 |
193
+ | No log | 3.55 | 284 | 0.6622 | 0.5422 | 0.6622 | 0.8137 |
194
+ | No log | 3.575 | 286 | 0.8135 | 0.5294 | 0.8135 | 0.9019 |
195
+ | No log | 3.6 | 288 | 0.9643 | 0.5339 | 0.9643 | 0.9820 |
196
+ | No log | 3.625 | 290 | 0.9790 | 0.5075 | 0.9790 | 0.9895 |
197
+ | No log | 3.65 | 292 | 0.7961 | 0.5210 | 0.7961 | 0.8923 |
198
+ | No log | 3.675 | 294 | 0.6942 | 0.5697 | 0.6942 | 0.8332 |
199
+ | No log | 3.7 | 296 | 0.6822 | 0.5516 | 0.6822 | 0.8259 |
200
+ | No log | 3.725 | 298 | 0.7211 | 0.5888 | 0.7211 | 0.8492 |
201
+ | No log | 3.75 | 300 | 0.8477 | 0.4994 | 0.8477 | 0.9207 |
202
+ | No log | 3.775 | 302 | 0.8452 | 0.5013 | 0.8452 | 0.9194 |
203
+ | No log | 3.8 | 304 | 0.8141 | 0.5041 | 0.8141 | 0.9023 |
204
+ | No log | 3.825 | 306 | 0.7848 | 0.5777 | 0.7848 | 0.8859 |
205
+ | No log | 3.85 | 308 | 0.7577 | 0.5777 | 0.7577 | 0.8704 |
206
+ | No log | 3.875 | 310 | 0.7528 | 0.5938 | 0.7528 | 0.8677 |
207
+ | No log | 3.9 | 312 | 0.6759 | 0.5588 | 0.6759 | 0.8221 |
208
+ | No log | 3.925 | 314 | 0.6354 | 0.6239 | 0.6354 | 0.7971 |
209
+ | No log | 3.95 | 316 | 0.6383 | 0.6046 | 0.6383 | 0.7989 |
210
+ | No log | 3.975 | 318 | 0.6506 | 0.5943 | 0.6506 | 0.8066 |
211
+ | No log | 4.0 | 320 | 0.6880 | 0.5331 | 0.6880 | 0.8295 |
212
+ | No log | 4.025 | 322 | 0.7763 | 0.4926 | 0.7763 | 0.8811 |
213
+ | No log | 4.05 | 324 | 1.0260 | 0.5168 | 1.0260 | 1.0129 |
214
+ | No log | 4.075 | 326 | 1.1306 | 0.4094 | 1.1306 | 1.0633 |
215
+ | No log | 4.1 | 328 | 0.9477 | 0.5 | 0.9477 | 0.9735 |
216
+ | No log | 4.125 | 330 | 0.7750 | 0.5718 | 0.7750 | 0.8803 |
217
+ | No log | 4.15 | 332 | 0.7066 | 0.5917 | 0.7066 | 0.8406 |
218
+ | No log | 4.175 | 334 | 0.7035 | 0.5517 | 0.7035 | 0.8388 |
219
+ | No log | 4.2 | 336 | 0.7150 | 0.5798 | 0.7150 | 0.8456 |
220
+ | No log | 4.225 | 338 | 0.7051 | 0.5798 | 0.7051 | 0.8397 |
221
+ | No log | 4.25 | 340 | 0.7183 | 0.5477 | 0.7183 | 0.8475 |
222
+ | No log | 4.275 | 342 | 0.6710 | 0.6014 | 0.6710 | 0.8191 |
223
+ | No log | 4.3 | 344 | 0.6596 | 0.5891 | 0.6596 | 0.8122 |
224
+ | No log | 4.325 | 346 | 0.6928 | 0.5763 | 0.6928 | 0.8323 |
225
+ | No log | 4.35 | 348 | 0.7987 | 0.5344 | 0.7987 | 0.8937 |
226
+ | No log | 4.375 | 350 | 0.8619 | 0.5625 | 0.8619 | 0.9284 |
227
+ | No log | 4.4 | 352 | 0.8029 | 0.5344 | 0.8029 | 0.8960 |
228
+ | No log | 4.425 | 354 | 0.6756 | 0.5975 | 0.6756 | 0.8220 |
229
+ | No log | 4.45 | 356 | 0.6340 | 0.6364 | 0.6340 | 0.7962 |
230
+ | No log | 4.475 | 358 | 0.6326 | 0.6401 | 0.6326 | 0.7953 |
231
+ | No log | 4.5 | 360 | 0.6346 | 0.6820 | 0.6346 | 0.7966 |
232
+ | No log | 4.525 | 362 | 0.6490 | 0.6444 | 0.6490 | 0.8056 |
233
+ | No log | 4.55 | 364 | 0.6394 | 0.6969 | 0.6394 | 0.7996 |
234
+ | No log | 4.575 | 366 | 0.6196 | 0.6976 | 0.6196 | 0.7872 |
235
+ | No log | 4.6 | 368 | 0.6293 | 0.6426 | 0.6293 | 0.7933 |
236
+ | No log | 4.625 | 370 | 0.6531 | 0.5066 | 0.6531 | 0.8082 |
237
+ | No log | 4.65 | 372 | 0.6668 | 0.4428 | 0.6668 | 0.8166 |
238
+ | No log | 4.675 | 374 | 0.6906 | 0.5113 | 0.6906 | 0.8310 |
239
+ | No log | 4.7 | 376 | 0.7409 | 0.5356 | 0.7409 | 0.8608 |
240
+ | No log | 4.725 | 378 | 0.7983 | 0.5331 | 0.7983 | 0.8935 |
241
+ | No log | 4.75 | 380 | 0.8252 | 0.5106 | 0.8252 | 0.9084 |
242
+ | No log | 4.775 | 382 | 0.7865 | 0.5266 | 0.7865 | 0.8868 |
243
+ | No log | 4.8 | 384 | 0.7565 | 0.5157 | 0.7565 | 0.8698 |
244
+ | No log | 4.825 | 386 | 0.6979 | 0.5798 | 0.6979 | 0.8354 |
245
+ | No log | 4.85 | 388 | 0.6647 | 0.5798 | 0.6647 | 0.8153 |
246
+ | No log | 4.875 | 390 | 0.6388 | 0.7101 | 0.6388 | 0.7993 |
247
+ | No log | 4.9 | 392 | 0.6212 | 0.7012 | 0.6212 | 0.7881 |
248
+ | No log | 4.925 | 394 | 0.6258 | 0.6630 | 0.6258 | 0.7911 |
249
+ | No log | 4.95 | 396 | 0.6348 | 0.6543 | 0.6348 | 0.7967 |
250
+ | No log | 4.975 | 398 | 0.6227 | 0.6995 | 0.6227 | 0.7891 |
251
+ | No log | 5.0 | 400 | 0.7156 | 0.5666 | 0.7156 | 0.8459 |
252
+ | No log | 5.025 | 402 | 0.8185 | 0.5331 | 0.8185 | 0.9047 |
253
+ | No log | 5.05 | 404 | 0.8719 | 0.4898 | 0.8719 | 0.9337 |
254
+ | No log | 5.075 | 406 | 0.9023 | 0.4898 | 0.9023 | 0.9499 |
255
+ | No log | 5.1 | 408 | 0.9027 | 0.4573 | 0.9027 | 0.9501 |
256
+ | No log | 5.125 | 410 | 0.8930 | 0.4573 | 0.8930 | 0.9450 |
257
+ | No log | 5.15 | 412 | 0.8961 | 0.4796 | 0.8961 | 0.9466 |
258
+ | No log | 5.175 | 414 | 0.8889 | 0.4796 | 0.8889 | 0.9428 |
259
+ | No log | 5.2 | 416 | 0.9171 | 0.4781 | 0.9171 | 0.9577 |
260
+ | No log | 5.225 | 418 | 0.9707 | 0.4668 | 0.9707 | 0.9853 |
261
+ | No log | 5.25 | 420 | 0.9091 | 0.5295 | 0.9091 | 0.9535 |
262
+ | No log | 5.275 | 422 | 0.8632 | 0.4681 | 0.8632 | 0.9291 |
263
+ | No log | 5.3 | 424 | 0.7910 | 0.5253 | 0.7910 | 0.8894 |
264
+ | No log | 5.325 | 426 | 0.7815 | 0.5157 | 0.7815 | 0.8840 |
265
+ | No log | 5.35 | 428 | 0.8061 | 0.5253 | 0.8061 | 0.8978 |
266
+ | No log | 5.375 | 430 | 0.8236 | 0.5253 | 0.8236 | 0.9075 |
267
+ | No log | 5.4 | 432 | 0.7738 | 0.5372 | 0.7738 | 0.8797 |
268
+ | No log | 5.425 | 434 | 0.7095 | 0.5509 | 0.7095 | 0.8423 |
269
+ | No log | 5.45 | 436 | 0.7486 | 0.5891 | 0.7486 | 0.8652 |
270
+ | No log | 5.475 | 438 | 0.7648 | 0.5526 | 0.7648 | 0.8746 |
271
+ | No log | 5.5 | 440 | 0.6686 | 0.6015 | 0.6686 | 0.8177 |
272
+ | No log | 5.525 | 442 | 0.6139 | 0.6301 | 0.6139 | 0.7835 |
273
+ | No log | 5.55 | 444 | 0.6068 | 0.6301 | 0.6068 | 0.7789 |
274
+ | No log | 5.575 | 446 | 0.6226 | 0.6228 | 0.6226 | 0.7890 |
275
+ | No log | 5.6 | 448 | 0.6672 | 0.6310 | 0.6672 | 0.8168 |
276
+ | No log | 5.625 | 450 | 0.6875 | 0.5385 | 0.6875 | 0.8292 |
277
+ | No log | 5.65 | 452 | 0.6685 | 0.5534 | 0.6685 | 0.8176 |
278
+ | No log | 5.675 | 454 | 0.6894 | 0.4966 | 0.6894 | 0.8303 |
279
+ | No log | 5.7 | 456 | 0.7292 | 0.5062 | 0.7292 | 0.8540 |
280
+ | No log | 5.725 | 458 | 0.7928 | 0.5332 | 0.7928 | 0.8904 |
281
+ | No log | 5.75 | 460 | 0.7484 | 0.5346 | 0.7484 | 0.8651 |
282
+ | No log | 5.775 | 462 | 0.6655 | 0.5651 | 0.6655 | 0.8158 |
283
+ | No log | 5.8 | 464 | 0.6204 | 0.5361 | 0.6204 | 0.7876 |
284
+ | No log | 5.825 | 466 | 0.6365 | 0.5103 | 0.6365 | 0.7978 |
285
+ | No log | 5.85 | 468 | 0.7272 | 0.5319 | 0.7272 | 0.8528 |
286
+ | No log | 5.875 | 470 | 0.8898 | 0.5391 | 0.8898 | 0.9433 |
287
+ | No log | 5.9 | 472 | 0.9222 | 0.5484 | 0.9222 | 0.9603 |
288
+ | No log | 5.925 | 474 | 0.8640 | 0.5484 | 0.8640 | 0.9295 |
289
+ | No log | 5.95 | 476 | 0.7342 | 0.5307 | 0.7342 | 0.8568 |
290
+ | No log | 5.975 | 478 | 0.6311 | 0.6188 | 0.6311 | 0.7944 |
291
+ | No log | 6.0 | 480 | 0.6146 | 0.6003 | 0.6146 | 0.7840 |
292
+ | No log | 6.025 | 482 | 0.6270 | 0.5898 | 0.6270 | 0.7918 |
293
+ | No log | 6.05 | 484 | 0.7006 | 0.5479 | 0.7006 | 0.8370 |
294
+ | No log | 6.075 | 486 | 0.7587 | 0.5360 | 0.7587 | 0.8710 |
295
+ | No log | 6.1 | 488 | 0.7755 | 0.5644 | 0.7755 | 0.8806 |
296
+ | No log | 6.125 | 490 | 0.7424 | 0.5756 | 0.7424 | 0.8616 |
297
+ | No log | 6.15 | 492 | 0.7121 | 0.5521 | 0.7121 | 0.8439 |
298
+ | No log | 6.175 | 494 | 0.6245 | 0.6099 | 0.6245 | 0.7903 |
299
+ | No log | 6.2 | 496 | 0.5524 | 0.6805 | 0.5524 | 0.7433 |
300
+ | No log | 6.225 | 498 | 0.5385 | 0.7090 | 0.5385 | 0.7338 |
301
+ | 0.2913 | 6.25 | 500 | 0.5578 | 0.7131 | 0.5578 | 0.7469 |
302
+ | 0.2913 | 6.275 | 502 | 0.5632 | 0.6881 | 0.5632 | 0.7505 |
303
+ | 0.2913 | 6.3 | 504 | 0.5591 | 0.7012 | 0.5591 | 0.7477 |
304
+ | 0.2913 | 6.325 | 506 | 0.5702 | 0.6672 | 0.5702 | 0.7551 |
305
+ | 0.2913 | 6.35 | 508 | 0.5610 | 0.7469 | 0.5610 | 0.7490 |
306
+ | 0.2913 | 6.375 | 510 | 0.5590 | 0.7136 | 0.5590 | 0.7477 |
307
+ | 0.2913 | 6.4 | 512 | 0.5596 | 0.7136 | 0.5596 | 0.7481 |
308
+ | 0.2913 | 6.425 | 514 | 0.5738 | 0.6944 | 0.5738 | 0.7575 |
309
+ | 0.2913 | 6.45 | 516 | 0.6086 | 0.6207 | 0.6086 | 0.7801 |
310
+ | 0.2913 | 6.475 | 518 | 0.6176 | 0.6073 | 0.6176 | 0.7859 |
311
+ | 0.2913 | 6.5 | 520 | 0.6294 | 0.5777 | 0.6294 | 0.7933 |
312
+ | 0.2913 | 6.525 | 522 | 0.6063 | 0.6348 | 0.6063 | 0.7787 |
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 sha256:3b1d2982331c4bb6fe6f312a4450e259aa432dd7f72a82d97eaa92b9cbe3f21f
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8bf622b8e5aa6de6662daacd16172bdb6386a9ae76ddca6e207354f22b033e2a
3
+ size 5304