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e2e-flan-large-noscore

Transformers
PyTorch
t5
text2text-generation
text-generation-inference
Model card Files
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README.md ADDED
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+ <table>
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+ <thead>
3
+ <tr>
4
+ <th>Epoch</th>
5
+ <th>Training Loss</th>
6
+ <th>Validation Loss</th>
7
+ <th>Rouge1</th>
8
+ <th>Rouge2</th>
9
+ <th>Rougel</th>
10
+ <th>Rougelsum</th>
11
+ <th>Gen Len</th>
12
+ </tr>
13
+ </thead>
14
+ <tbody>
15
+ <tr>
16
+ <td>45</td>
17
+ <td>0.354900</td>
18
+ <td>0.269528</td>
19
+ <td>0.576800</td>
20
+ <td>0.401800</td>
21
+ <td>0.459100</td>
22
+ <td>0.568700</td>
23
+ <td>477.000000</td>
24
+ </tr>
25
+ <tr>
26
+ <td>46</td>
27
+ <td>0.336500</td>
28
+ <td>0.266415</td>
29
+ <td>0.589300</td>
30
+ <td>0.407500</td>
31
+ <td>0.462300</td>
32
+ <td>0.578900</td>
33
+ <td>531.588200</td>
34
+ </tr>
35
+ <tr>
36
+ <td>47</td>
37
+ <td>0.330200</td>
38
+ <td>0.264836</td>
39
+ <td>0.527300</td>
40
+ <td>0.359300</td>
41
+ <td>0.419800</td>
42
+ <td>0.519300</td>
43
+ <td>602.764700</td>
44
+ </tr>
45
+ <tr>
46
+ <td>49</td>
47
+ <td>0.326100</td>
48
+ <td>0.263734</td>
49
+ <td>0.562700</td>
50
+ <td>0.399900</td>
51
+ <td>0.458800</td>
52
+ <td>0.556100</td>
53
+ <td>562.941200</td>
54
+ </tr>
55
+ <tr>
56
+ <td>49</td>
57
+ <td>0.326700</td>
58
+ <td>0.262347</td>
59
+ <td>0.585700</td>
60
+ <td>0.413500</td>
61
+ <td>0.474000</td>
62
+ <td>0.577500</td>
63
+ <td>545.882400</td>
64
+ </tr>
65
+ <tr>
66
+ <td>50</td>
67
+ <td>0.319400</td>
68
+ <td>0.261993</td>
69
+ <td>0.581300</td>
70
+ <td>0.411200</td>
71
+ <td>0.471100</td>
72
+ <td>0.570000</td>
73
+ <td>555.941200</td>
74
+ </tr>
75
+ <tr>
76
+ <td>51</td>
77
+ <td>0.314700</td>
78
+ <td>0.261653</td>
79
+ <td>0.586700</td>
80
+ <td>0.415300</td>
81
+ <td>0.473400</td>
82
+ <td>0.578600</td>
83
+ <td>543.529400</td>
84
+ </tr>
85
+ <tr>
86
+ <td>53</td>
87
+ <td>0.311900</td>
88
+ <td>0.261087</td>
89
+ <td>0.617900</td>
90
+ <td>0.433900</td>
91
+ <td>0.489800</td>
92
+ <td>0.608700</td>
93
+ <td>525.647100</td>
94
+ </tr>
95
+ <tr>
96
+ <td>53</td>
97
+ <td>0.315600</td>
98
+ <td>0.260690</td>
99
+ <td>0.616000</td>
100
+ <td>0.434500</td>
101
+ <td>0.492100</td>
102
+ <td>0.606800</td>
103
+ <td>529.588200</td>
104
+ </tr>
105
+ <tr>
106
+ <td>54</td>
107
+ <td>0.315400</td>
108
+ <td>0.260348</td>
109
+ <td>0.615600</td>
110
+ <td>0.432100</td>
111
+ <td>0.489000</td>
112
+ <td>0.605500</td>
113
+ <td>535.411800</td>
114
+ </tr>
115
+ <tr>
116
+ <td>55</td>
117
+ <td>0.307700</td>
118
+ <td>0.259774</td>
119
+ <td>0.622600</td>
120
+ <td>0.443800</td>
121
+ <td>0.497700</td>
122
+ <td>0.613200</td>
123
+ <td>529.647100</td>
124
+ </tr>
125
+ <tr>
126
+ <td>56</td>
127
+ <td>0.306800</td>
128
+ <td>0.259790</td>
129
+ <td>0.620900</td>
130
+ <td>0.438100</td>
131
+ <td>0.493000</td>
132
+ <td>0.610600</td>
133
+ <td>515.058800</td>
134
+ </tr>
135
+ <tr>
136
+ <td>58</td>
137
+ <td>0.305700</td>
138
+ <td>0.259624</td>
139
+ <td>0.618500</td>
140
+ <td>0.434000</td>
141
+ <td>0.489200</td>
142
+ <td>0.607800</td>
143
+ <td>506.352900</td>
144
+ </tr>
145
+ <tr>
146
+ <td>58</td>
147
+ <td>0.310700</td>
148
+ <td>0.259519</td>
149
+ <td>0.618800</td>
150
+ <td>0.434700</td>
151
+ <td>0.489100</td>
152
+ <td>0.608000</td>
153
+ <td>506.529400</td>
154
+ </tr>
155
+ <tr>
156
+ <td>59</td>
157
+ <td>0.300900</td>
158
+ <td>0.259501</td>
159
+ <td>0.618800</td>
160
+ <td>0.434700</td>
161
+ <td>0.489100</td>
162
+ <td>0.608000</td>
163
+ <td>506.529400</td>
164
+ </tr>
165
+ </table>
166
+