Hugging Face's logo

mnavas
/
beto-finetuned-token-reqadjzar

Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
María Navas Loro commited on
Commit
a811c65
•
1 Parent(s): 64a4fd0

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +263 -0
README.md ADDED
@@ -0,0 +1,263 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - generated_from_trainer
4
+ metrics:
5
+ - precision
6
+ - recall
7
+ - f1
8
+ - accuracy
9
+ model-index:
10
+ - name: beto-finetuned-token-reqadjzar
11
+ results: []
12
+ ---
13
+
14
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
17
+ # beto-finetuned-token-reqadjzar
18
+
19
+ This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 1.9170
22
+ - Precision: 0.1525
23
+ - Recall: 0.45
24
+ - F1: 0.2278
25
+ - Accuracy: 0.7971
26
+
27
+ ## Model description
28
+
29
+ More information needed
30
+
31
+ ## Intended uses & limitations
32
+
33
+ More information needed
34
+
35
+ ## Training and evaluation data
36
+
37
+ More information needed
38
+
39
+ ## Training procedure
40
+
41
+ ### Training hyperparameters
42
+
43
+ The following hyperparameters were used during training:
44
+ - learning_rate: 0.0001
45
+ - train_batch_size: 8
46
+ - eval_batch_size: 8
47
+ - seed: 42
48
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
+ - lr_scheduler_type: linear
50
+ - num_epochs: 200
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
55
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
56
+ | 0.8289 | 1.0 | 14 | 0.5344 | 0.0 | 0.0 | 0.0 | 0.7428 |
57
+ | 0.4847 | 2.0 | 28 | 0.4436 | 0.0 | 0.0 | 0.0 | 0.7546 |
58
+ | 0.3512 | 3.0 | 42 | 0.5584 | 0.0 | 0.0 | 0.0 | 0.7643 |
59
+ | 0.2789 | 4.0 | 56 | 0.5861 | 0.0 | 0.0 | 0.0 | 0.8250 |
60
+ | 0.185 | 5.0 | 70 | 0.7569 | 0.0606 | 0.2 | 0.0930 | 0.7602 |
61
+ | 0.1408 | 6.0 | 84 | 0.9035 | 0.0678 | 0.2 | 0.1013 | 0.7775 |
62
+ | 0.1417 | 7.0 | 98 | 0.6097 | 0.0755 | 0.2 | 0.1096 | 0.8311 |
63
+ | 0.0693 | 8.0 | 112 | 0.9226 | 0.1061 | 0.35 | 0.1628 | 0.7727 |
64
+ | 0.0571 | 9.0 | 126 | 0.6895 | 0.0769 | 0.2 | 0.1111 | 0.8 |
65
+ | 0.0414 | 10.0 | 140 | 1.0235 | 0.1698 | 0.45 | 0.2466 | 0.8131 |
66
+ | 0.0276 | 11.0 | 154 | 0.9588 | 0.1628 | 0.35 | 0.2222 | 0.8054 |
67
+ | 0.0265 | 12.0 | 168 | 1.1193 | 0.0882 | 0.3 | 0.1364 | 0.7751 |
68
+ | 0.0277 | 13.0 | 182 | 1.3907 | 0.1579 | 0.45 | 0.2338 | 0.7878 |
69
+ | 0.0216 | 14.0 | 196 | 1.2417 | 0.1311 | 0.4 | 0.1975 | 0.7825 |
70
+ | 0.0261 | 15.0 | 210 | 1.1495 | 0.1429 | 0.4 | 0.2105 | 0.8071 |
71
+ | 0.019 | 16.0 | 224 | 1.5922 | 0.1475 | 0.45 | 0.2222 | 0.7508 |
72
+ | 0.0274 | 17.0 | 238 | 1.1795 | 0.1176 | 0.4 | 0.1818 | 0.8045 |
73
+ | 0.0198 | 18.0 | 252 | 1.2508 | 0.1053 | 0.4 | 0.1667 | 0.7848 |
74
+ | 0.0136 | 19.0 | 266 | 1.1545 | 0.1695 | 0.5 | 0.2532 | 0.7899 |
75
+ | 0.0084 | 20.0 | 280 | 1.4068 | 0.2051 | 0.4 | 0.2712 | 0.8276 |
76
+ | 0.0051 | 21.0 | 294 | 1.5559 | 0.1667 | 0.4 | 0.2353 | 0.8170 |
77
+ | 0.0064 | 22.0 | 308 | 1.7301 | 0.1220 | 0.5 | 0.1961 | 0.7875 |
78
+ | 0.0032 | 23.0 | 322 | 1.5436 | 0.1957 | 0.45 | 0.2727 | 0.8198 |
79
+ | 0.0023 | 24.0 | 336 | 1.7796 | 0.1364 | 0.45 | 0.2093 | 0.7846 |
80
+ | 0.0076 | 25.0 | 350 | 1.7765 | 0.1923 | 0.5 | 0.2778 | 0.7943 |
81
+ | 0.0056 | 26.0 | 364 | 1.6022 | 0.2759 | 0.4 | 0.3265 | 0.8211 |
82
+ | 0.0194 | 27.0 | 378 | 1.1911 | 0.1346 | 0.35 | 0.1944 | 0.8394 |
83
+ | 0.0286 | 28.0 | 392 | 1.2321 | 0.1739 | 0.4 | 0.2424 | 0.7839 |
84
+ | 0.0095 | 29.0 | 406 | 1.3354 | 0.1695 | 0.5 | 0.2532 | 0.7623 |
85
+ | 0.0031 | 30.0 | 420 | 1.6826 | 0.1724 | 0.5 | 0.2564 | 0.7543 |
86
+ | 0.0017 | 31.0 | 434 | 1.7094 | 0.1607 | 0.45 | 0.2368 | 0.7834 |
87
+ | 0.0023 | 32.0 | 448 | 1.7899 | 0.1538 | 0.4 | 0.2222 | 0.7694 |
88
+ | 0.0016 | 33.0 | 462 | 1.7496 | 0.1698 | 0.45 | 0.2466 | 0.7766 |
89
+ | 0.0017 | 34.0 | 476 | 1.8328 | 0.1818 | 0.5 | 0.2667 | 0.7677 |
90
+ | 0.0026 | 35.0 | 490 | 2.0814 | 0.1875 | 0.45 | 0.2647 | 0.7594 |
91
+ | 0.0088 | 36.0 | 504 | 1.5723 | 0.12 | 0.45 | 0.1895 | 0.7570 |
92
+ | 0.0031 | 37.0 | 518 | 1.4726 | 0.1569 | 0.4 | 0.2254 | 0.8006 |
93
+ | 0.0064 | 38.0 | 532 | 2.4796 | 0.2759 | 0.4 | 0.3265 | 0.7287 |
94
+ | 0.0032 | 39.0 | 546 | 2.0958 | 0.1186 | 0.35 | 0.1772 | 0.7339 |
95
+ | 0.0024 | 40.0 | 560 | 2.1926 | 0.2162 | 0.4 | 0.2807 | 0.7487 |
96
+ | 0.0117 | 41.0 | 574 | 1.9346 | 0.1961 | 0.5 | 0.2817 | 0.7213 |
97
+ | 0.053 | 42.0 | 588 | 2.4844 | 0.2333 | 0.35 | 0.28 | 0.7317 |
98
+ | 0.0172 | 43.0 | 602 | 1.1900 | 0.1148 | 0.35 | 0.1728 | 0.8118 |
99
+ | 0.0084 | 44.0 | 616 | 1.3718 | 0.1515 | 0.5 | 0.2326 | 0.8115 |
100
+ | 0.0141 | 45.0 | 630 | 1.3623 | 0.1356 | 0.4 | 0.2025 | 0.7938 |
101
+ | 0.0044 | 46.0 | 644 | 1.2805 | 0.1552 | 0.45 | 0.2308 | 0.8080 |
102
+ | 0.0031 | 47.0 | 658 | 1.8072 | 0.1636 | 0.45 | 0.24 | 0.7946 |
103
+ | 0.0066 | 48.0 | 672 | 2.3164 | 0.1892 | 0.35 | 0.2456 | 0.7154 |
104
+ | 0.002 | 49.0 | 686 | 2.2669 | 0.175 | 0.35 | 0.2333 | 0.7380 |
105
+ | 0.0033 | 50.0 | 700 | 1.5042 | 0.1385 | 0.45 | 0.2118 | 0.7997 |
106
+ | 0.0027 | 51.0 | 714 | 1.3601 | 0.1515 | 0.5 | 0.2326 | 0.8225 |
107
+ | 0.0025 | 52.0 | 728 | 1.4208 | 0.1698 | 0.45 | 0.2466 | 0.8018 |
108
+ | 0.0048 | 53.0 | 742 | 1.5204 | 0.1636 | 0.45 | 0.24 | 0.8030 |
109
+ | 0.0046 | 54.0 | 756 | 1.6875 | 0.1429 | 0.45 | 0.2169 | 0.7842 |
110
+ | 0.0052 | 55.0 | 770 | 1.4927 | 0.1739 | 0.4 | 0.2424 | 0.8201 |
111
+ | 0.0055 | 56.0 | 784 | 1.3876 | 0.1731 | 0.45 | 0.25 | 0.8084 |
112
+ | 0.0027 | 57.0 | 798 | 1.4384 | 0.1702 | 0.4 | 0.2388 | 0.8163 |
113
+ | 0.0019 | 58.0 | 812 | 1.6044 | 0.1569 | 0.4 | 0.2254 | 0.8205 |
114
+ | 0.0012 | 59.0 | 826 | 1.6617 | 0.1538 | 0.4 | 0.2222 | 0.8208 |
115
+ | 0.0009 | 60.0 | 840 | 1.6607 | 0.225 | 0.45 | 0.3 | 0.8164 |
116
+ | 0.0012 | 61.0 | 854 | 1.5158 | 0.1818 | 0.4 | 0.2500 | 0.8195 |
117
+ | 0.0011 | 62.0 | 868 | 1.5161 | 0.2 | 0.45 | 0.2769 | 0.8225 |
118
+ | 0.0009 | 63.0 | 882 | 1.5669 | 0.2045 | 0.45 | 0.2813 | 0.8232 |
119
+ | 0.0008 | 64.0 | 896 | 1.5988 | 0.2045 | 0.45 | 0.2813 | 0.8237 |
120
+ | 0.0011 | 65.0 | 910 | 1.5689 | 0.2195 | 0.45 | 0.2951 | 0.8243 |
121
+ | 0.0008 | 66.0 | 924 | 1.5746 | 0.225 | 0.45 | 0.3 | 0.8243 |
122
+ | 0.0009 | 67.0 | 938 | 1.5815 | 0.2045 | 0.45 | 0.2813 | 0.8235 |
123
+ | 0.0007 | 68.0 | 952 | 1.5532 | 0.1739 | 0.4 | 0.2424 | 0.8232 |
124
+ | 0.0009 | 69.0 | 966 | 1.5724 | 0.1702 | 0.4 | 0.2388 | 0.8238 |
125
+ | 0.0008 | 70.0 | 980 | 1.6021 | 0.1778 | 0.4 | 0.2462 | 0.8238 |
126
+ | 0.0008 | 71.0 | 994 | 1.6159 | 0.1778 | 0.4 | 0.2462 | 0.8238 |
127
+ | 0.0007 | 72.0 | 1008 | 1.6047 | 0.1702 | 0.4 | 0.2388 | 0.8232 |
128
+ | 0.0007 | 73.0 | 1022 | 1.6468 | 0.2 | 0.45 | 0.2769 | 0.8217 |
129
+ | 0.0007 | 74.0 | 1036 | 1.6592 | 0.2093 | 0.45 | 0.2857 | 0.8222 |
130
+ | 0.0008 | 75.0 | 1050 | 1.6642 | 0.2143 | 0.45 | 0.2903 | 0.8220 |
131
+ | 0.0008 | 76.0 | 1064 | 1.6042 | 0.2195 | 0.45 | 0.2951 | 0.8244 |
132
+ | 0.0007 | 77.0 | 1078 | 1.5905 | 0.225 | 0.45 | 0.3 | 0.8247 |
133
+ | 0.001 | 78.0 | 1092 | 1.6081 | 0.225 | 0.45 | 0.3 | 0.8249 |
134
+ | 0.0007 | 79.0 | 1106 | 1.6255 | 0.225 | 0.45 | 0.3 | 0.8249 |
135
+ | 0.0007 | 80.0 | 1120 | 1.6583 | 0.2093 | 0.45 | 0.2857 | 0.8270 |
136
+ | 0.0009 | 81.0 | 1134 | 1.5953 | 0.2308 | 0.45 | 0.3051 | 0.8261 |
137
+ | 0.0012 | 82.0 | 1148 | 1.9475 | 0.1216 | 0.45 | 0.1915 | 0.7919 |
138
+ | 0.0025 | 83.0 | 1162 | 1.8182 | 0.1098 | 0.45 | 0.1765 | 0.7929 |
139
+ | 0.01 | 84.0 | 1176 | 1.7011 | 0.2051 | 0.4 | 0.2712 | 0.8033 |
140
+ | 0.0025 | 85.0 | 1190 | 1.6036 | 0.1493 | 0.5 | 0.2299 | 0.7790 |
141
+ | 0.0099 | 86.0 | 1204 | 1.9946 | 0.25 | 0.4 | 0.3077 | 0.7787 |
142
+ | 0.0037 | 87.0 | 1218 | 1.4567 | 0.1356 | 0.4 | 0.2025 | 0.7821 |
143
+ | 0.0044 | 88.0 | 1232 | 1.4056 | 0.1778 | 0.4 | 0.2462 | 0.8109 |
144
+ | 0.0025 | 89.0 | 1246 | 1.5609 | 0.1628 | 0.35 | 0.2222 | 0.7573 |
145
+ | 0.0026 | 90.0 | 1260 | 1.5755 | 0.1739 | 0.4 | 0.2424 | 0.7732 |
146
+ | 0.003 | 91.0 | 1274 | 1.5189 | 0.2812 | 0.45 | 0.3462 | 0.7831 |
147
+ | 0.0015 | 92.0 | 1288 | 1.5804 | 0.1169 | 0.45 | 0.1856 | 0.7707 |
148
+ | 0.0012 | 93.0 | 1302 | 1.4188 | 0.2195 | 0.45 | 0.2951 | 0.8054 |
149
+ | 0.0047 | 94.0 | 1316 | 1.4388 | 0.2174 | 0.5 | 0.3030 | 0.7992 |
150
+ | 0.0009 | 95.0 | 1330 | 1.5773 | 0.1667 | 0.45 | 0.2432 | 0.7958 |
151
+ | 0.0011 | 96.0 | 1344 | 1.5059 | 0.1837 | 0.45 | 0.2609 | 0.8 |
152
+ | 0.001 | 97.0 | 1358 | 1.5438 | 0.1731 | 0.45 | 0.25 | 0.7891 |
153
+ | 0.0007 | 98.0 | 1372 | 1.6020 | 0.1552 | 0.45 | 0.2308 | 0.7947 |
154
+ | 0.0009 | 99.0 | 1386 | 1.6698 | 0.2 | 0.45 | 0.2769 | 0.7881 |
155
+ | 0.001 | 100.0 | 1400 | 1.7616 | 0.1875 | 0.45 | 0.2647 | 0.7554 |
156
+ | 0.0007 | 101.0 | 1414 | 1.8242 | 0.2 | 0.45 | 0.2769 | 0.7554 |
157
+ | 0.0007 | 102.0 | 1428 | 1.8466 | 0.2 | 0.45 | 0.2769 | 0.7555 |
158
+ | 0.0008 | 103.0 | 1442 | 1.8634 | 0.2045 | 0.45 | 0.2813 | 0.7555 |
159
+ | 0.0007 | 104.0 | 1456 | 1.9182 | 0.2045 | 0.45 | 0.2813 | 0.7555 |
160
+ | 0.0007 | 105.0 | 1470 | 1.9461 | 0.2093 | 0.45 | 0.2857 | 0.7552 |
161
+ | 0.0007 | 106.0 | 1484 | 1.9311 | 0.2143 | 0.45 | 0.2903 | 0.7558 |
162
+ | 0.0009 | 107.0 | 1498 | 1.9476 | 0.2143 | 0.45 | 0.2903 | 0.7558 |
163
+ | 0.0006 | 108.0 | 1512 | 1.9806 | 0.2195 | 0.45 | 0.2951 | 0.7548 |
164
+ | 0.0007 | 109.0 | 1526 | 2.0085 | 0.2045 | 0.45 | 0.2813 | 0.7543 |
165
+ | 0.0008 | 110.0 | 1540 | 2.0216 | 0.2 | 0.45 | 0.2769 | 0.7540 |
166
+ | 0.0008 | 111.0 | 1554 | 2.0290 | 0.2 | 0.45 | 0.2769 | 0.7544 |
167
+ | 0.0007 | 112.0 | 1568 | 2.0131 | 0.2 | 0.45 | 0.2769 | 0.7537 |
168
+ | 0.0007 | 113.0 | 1582 | 2.0182 | 0.2 | 0.45 | 0.2769 | 0.7537 |
169
+ | 0.0007 | 114.0 | 1596 | 2.0345 | 0.1957 | 0.45 | 0.2727 | 0.7534 |
170
+ | 0.0006 | 115.0 | 1610 | 2.0338 | 0.2 | 0.45 | 0.2769 | 0.7532 |
171
+ | 0.0007 | 116.0 | 1624 | 2.0445 | 0.2 | 0.45 | 0.2769 | 0.7531 |
172
+ | 0.0007 | 117.0 | 1638 | 2.0688 | 0.2143 | 0.45 | 0.2903 | 0.7526 |
173
+ | 0.0008 | 118.0 | 1652 | 2.0920 | 0.225 | 0.45 | 0.3 | 0.7541 |
174
+ | 0.0009 | 119.0 | 1666 | 2.1148 | 0.225 | 0.45 | 0.3 | 0.7540 |
175
+ | 0.0008 | 120.0 | 1680 | 2.0795 | 0.18 | 0.45 | 0.2571 | 0.7534 |
176
+ | 0.001 | 121.0 | 1694 | 2.0217 | 0.2 | 0.45 | 0.2769 | 0.7548 |
177
+ | 0.0013 | 122.0 | 1708 | 1.9480 | 0.1698 | 0.45 | 0.2466 | 0.7615 |
178
+ | 0.0009 | 123.0 | 1722 | 1.8774 | 0.2 | 0.45 | 0.2769 | 0.7677 |
179
+ | 0.0009 | 124.0 | 1736 | 1.7994 | 0.1304 | 0.45 | 0.2022 | 0.7837 |
180
+ | 0.0007 | 125.0 | 1750 | 1.7864 | 0.18 | 0.45 | 0.2571 | 0.7967 |
181
+ | 0.0007 | 126.0 | 1764 | 1.7911 | 0.1837 | 0.45 | 0.2609 | 0.7971 |
182
+ | 0.0006 | 127.0 | 1778 | 1.8000 | 0.2 | 0.45 | 0.2769 | 0.7980 |
183
+ | 0.0007 | 128.0 | 1792 | 1.8162 | 0.2143 | 0.45 | 0.2903 | 0.7991 |
184
+ | 0.0007 | 129.0 | 1806 | 1.8334 | 0.2045 | 0.45 | 0.2813 | 0.7980 |
185
+ | 0.0007 | 130.0 | 1820 | 1.8374 | 0.2195 | 0.45 | 0.2951 | 0.7985 |
186
+ | 0.0007 | 131.0 | 1834 | 1.8494 | 0.2093 | 0.45 | 0.2857 | 0.7977 |
187
+ | 0.0006 | 132.0 | 1848 | 1.8593 | 0.2045 | 0.45 | 0.2813 | 0.7977 |
188
+ | 0.0007 | 133.0 | 1862 | 1.8704 | 0.2045 | 0.45 | 0.2813 | 0.7977 |
189
+ | 0.0007 | 134.0 | 1876 | 1.8739 | 0.1957 | 0.45 | 0.2727 | 0.7979 |
190
+ | 0.0006 | 135.0 | 1890 | 1.8806 | 0.1875 | 0.45 | 0.2647 | 0.7974 |
191
+ | 0.0007 | 136.0 | 1904 | 1.8789 | 0.1636 | 0.45 | 0.24 | 0.7961 |
192
+ | 0.0006 | 137.0 | 1918 | 1.8813 | 0.1579 | 0.45 | 0.2338 | 0.7962 |
193
+ | 0.0008 | 138.0 | 1932 | 1.8820 | 0.1667 | 0.45 | 0.2432 | 0.7944 |
194
+ | 0.0006 | 139.0 | 1946 | 1.8804 | 0.1579 | 0.45 | 0.2338 | 0.7937 |
195
+ | 0.0006 | 140.0 | 1960 | 1.8876 | 0.1552 | 0.45 | 0.2308 | 0.7919 |
196
+ | 0.0007 | 141.0 | 1974 | 1.8992 | 0.1343 | 0.45 | 0.2069 | 0.7867 |
197
+ | 0.0005 | 142.0 | 1988 | 1.9085 | 0.1579 | 0.45 | 0.2338 | 0.7922 |
198
+ | 0.0006 | 143.0 | 2002 | 1.9147 | 0.1607 | 0.45 | 0.2368 | 0.7922 |
199
+ | 0.0008 | 144.0 | 2016 | 1.9129 | 0.125 | 0.45 | 0.1957 | 0.7808 |
200
+ | 0.0007 | 145.0 | 2030 | 1.9075 | 0.1765 | 0.45 | 0.2535 | 0.7735 |
201
+ | 0.0007 | 146.0 | 2044 | 1.8986 | 0.15 | 0.45 | 0.2250 | 0.7885 |
202
+ | 0.0009 | 147.0 | 2058 | 1.8767 | 0.1579 | 0.45 | 0.2338 | 0.7911 |
203
+ | 0.0007 | 148.0 | 2072 | 1.8709 | 0.1385 | 0.45 | 0.2118 | 0.7875 |
204
+ | 0.0007 | 149.0 | 2086 | 1.8730 | 0.1364 | 0.45 | 0.2093 | 0.7885 |
205
+ | 0.0006 | 150.0 | 2100 | 1.8813 | 0.1406 | 0.45 | 0.2143 | 0.7879 |
206
+ | 0.0006 | 151.0 | 2114 | 1.8908 | 0.1607 | 0.45 | 0.2368 | 0.7899 |
207
+ | 0.0006 | 152.0 | 2128 | 1.9017 | 0.1636 | 0.45 | 0.24 | 0.7923 |
208
+ | 0.0007 | 153.0 | 2142 | 1.9101 | 0.1552 | 0.45 | 0.2308 | 0.7934 |
209
+ | 0.0007 | 154.0 | 2156 | 1.9167 | 0.1552 | 0.45 | 0.2308 | 0.7946 |
210
+ | 0.0006 | 155.0 | 2170 | 1.9177 | 0.1636 | 0.45 | 0.24 | 0.7917 |
211
+ | 0.0007 | 156.0 | 2184 | 1.9276 | 0.1552 | 0.45 | 0.2308 | 0.7893 |
212
+ | 0.0006 | 157.0 | 2198 | 1.9363 | 0.1429 | 0.45 | 0.2169 | 0.7878 |
213
+ | 0.0007 | 158.0 | 2212 | 1.9429 | 0.1324 | 0.45 | 0.2045 | 0.7866 |
214
+ | 0.0006 | 159.0 | 2226 | 1.9495 | 0.1525 | 0.45 | 0.2278 | 0.7891 |
215
+ | 0.0007 | 160.0 | 2240 | 1.9488 | 0.1364 | 0.45 | 0.2093 | 0.7866 |
216
+ | 0.0007 | 161.0 | 2254 | 1.9265 | 0.1667 | 0.45 | 0.2432 | 0.7914 |
217
+ | 0.0006 | 162.0 | 2268 | 1.9189 | 0.1698 | 0.45 | 0.2466 | 0.7928 |
218
+ | 0.0008 | 163.0 | 2282 | 1.9099 | 0.1579 | 0.45 | 0.2338 | 0.7941 |
219
+ | 0.0006 | 164.0 | 2296 | 1.9073 | 0.1607 | 0.45 | 0.2368 | 0.7941 |
220
+ | 0.0009 | 165.0 | 2310 | 1.8991 | 0.1698 | 0.45 | 0.2466 | 0.7929 |
221
+ | 0.0008 | 166.0 | 2324 | 1.8790 | 0.15 | 0.45 | 0.2250 | 0.7958 |
222
+ | 0.0006 | 167.0 | 2338 | 1.8819 | 0.1525 | 0.45 | 0.2278 | 0.7959 |
223
+ | 0.0007 | 168.0 | 2352 | 1.8877 | 0.1636 | 0.45 | 0.24 | 0.7955 |
224
+ | 0.0007 | 169.0 | 2366 | 1.8934 | 0.1731 | 0.45 | 0.25 | 0.7941 |
225
+ | 0.0007 | 170.0 | 2380 | 1.8959 | 0.18 | 0.45 | 0.2571 | 0.7935 |
226
+ | 0.0006 | 171.0 | 2394 | 1.9012 | 0.1765 | 0.45 | 0.2535 | 0.7934 |
227
+ | 0.0007 | 172.0 | 2408 | 1.9044 | 0.1837 | 0.45 | 0.2609 | 0.7928 |
228
+ | 0.0006 | 173.0 | 2422 | 1.9071 | 0.1765 | 0.45 | 0.2535 | 0.7931 |
229
+ | 0.0009 | 174.0 | 2436 | 1.9091 | 0.1837 | 0.45 | 0.2609 | 0.7923 |
230
+ | 0.0008 | 175.0 | 2450 | 1.9089 | 0.18 | 0.45 | 0.2571 | 0.7920 |
231
+ | 0.0006 | 176.0 | 2464 | 1.9076 | 0.1698 | 0.45 | 0.2466 | 0.7926 |
232
+ | 0.0007 | 177.0 | 2478 | 1.9079 | 0.1636 | 0.45 | 0.24 | 0.7920 |
233
+ | 0.0006 | 178.0 | 2492 | 1.9132 | 0.1765 | 0.45 | 0.2535 | 0.7922 |
234
+ | 0.0006 | 179.0 | 2506 | 1.9180 | 0.1698 | 0.45 | 0.2466 | 0.7917 |
235
+ | 0.0006 | 180.0 | 2520 | 1.9217 | 0.18 | 0.45 | 0.2571 | 0.7922 |
236
+ | 0.0006 | 181.0 | 2534 | 1.9161 | 0.1607 | 0.45 | 0.2368 | 0.7962 |
237
+ | 0.0006 | 182.0 | 2548 | 1.9178 | 0.1731 | 0.45 | 0.25 | 0.7997 |
238
+ | 0.0006 | 183.0 | 2562 | 1.9218 | 0.1765 | 0.45 | 0.2535 | 0.7998 |
239
+ | 0.0006 | 184.0 | 2576 | 1.9233 | 0.1765 | 0.45 | 0.2535 | 0.7998 |
240
+ | 0.0007 | 185.0 | 2590 | 1.9214 | 0.15 | 0.45 | 0.2250 | 0.7974 |
241
+ | 0.0007 | 186.0 | 2604 | 1.9203 | 0.1579 | 0.45 | 0.2338 | 0.7968 |
242
+ | 0.0007 | 187.0 | 2618 | 1.9115 | 0.15 | 0.45 | 0.2250 | 0.7988 |
243
+ | 0.0006 | 188.0 | 2632 | 1.9104 | 0.15 | 0.45 | 0.2250 | 0.7989 |
244
+ | 0.0006 | 189.0 | 2646 | 1.9120 | 0.15 | 0.45 | 0.2250 | 0.7989 |
245
+ | 0.0006 | 190.0 | 2660 | 1.9133 | 0.1552 | 0.45 | 0.2308 | 0.7992 |
246
+ | 0.0006 | 191.0 | 2674 | 1.9149 | 0.15 | 0.45 | 0.2250 | 0.7989 |
247
+ | 0.0007 | 192.0 | 2688 | 1.9145 | 0.15 | 0.45 | 0.2250 | 0.7989 |
248
+ | 0.0006 | 193.0 | 2702 | 1.9148 | 0.15 | 0.45 | 0.2250 | 0.7989 |
249
+ | 0.0006 | 194.0 | 2716 | 1.9147 | 0.1525 | 0.45 | 0.2278 | 0.7980 |
250
+ | 0.0006 | 195.0 | 2730 | 1.9144 | 0.1525 | 0.45 | 0.2278 | 0.7980 |
251
+ | 0.0006 | 196.0 | 2744 | 1.9157 | 0.15 | 0.45 | 0.2250 | 0.7979 |
252
+ | 0.0006 | 197.0 | 2758 | 1.9158 | 0.15 | 0.45 | 0.2250 | 0.7979 |
253
+ | 0.0006 | 198.0 | 2772 | 1.9167 | 0.1525 | 0.45 | 0.2278 | 0.7971 |
254
+ | 0.0007 | 199.0 | 2786 | 1.9166 | 0.1552 | 0.45 | 0.2308 | 0.7973 |
255
+ | 0.0006 | 200.0 | 2800 | 1.9170 | 0.1525 | 0.45 | 0.2278 | 0.7971 |
256
+
257
+
258
+ ### Framework versions
259
+
260
+ - Transformers 4.30.0.dev0
261
+ - Pytorch 2.0.0
262
+ - Datasets 2.1.0
263
+ - Tokenizers 0.13.3