Hugging Face's logo

SOham01
/
results

Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Model card Files
xet
Community
SOham01 commited on
Commit
2bf179e
·
verified ·
1 Parent(s): 28ea179

Model save

Browse files
Files changed (2) hide show
  1. README.md +432 -0
  2. generation_config.json +7 -0
README.md ADDED
@@ -0,0 +1,432 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: apache-2.0
4
+ base_model: t5-small
5
+ tags:
6
+ - generated_from_trainer
7
+ model-index:
8
+ - name: results
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # results
16
+
17
+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 3.5388
20
+
21
+ ## Model description
22
+
23
+ More information needed
24
+
25
+ ## Intended uses & limitations
26
+
27
+ More information needed
28
+
29
+ ## Training and evaluation data
30
+
31
+ More information needed
32
+
33
+ ## Training procedure
34
+
35
+ ### Training hyperparameters
36
+
37
+ The following hyperparameters were used during training:
38
+ - learning_rate: 5e-05
39
+ - train_batch_size: 8
40
+ - eval_batch_size: 8
41
+ - seed: 42
42
+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
43
+ - lr_scheduler_type: linear
44
+ - training_steps: 375
45
+
46
+ ### Training results
47
+
48
+ | Training Loss | Epoch | Step | Validation Loss |
49
+ |:-------------:|:-----:|:----:|:---------------:|
50
+ | No log | 1.0 | 1 | 10.3755 |
51
+ | No log | 2.0 | 2 | 8.9002 |
52
+ | No log | 3.0 | 3 | 7.5951 |
53
+ | No log | 4.0 | 4 | 6.5107 |
54
+ | No log | 5.0 | 5 | 5.7104 |
55
+ | No log | 6.0 | 6 | 5.2523 |
56
+ | No log | 7.0 | 7 | 5.0011 |
57
+ | No log | 8.0 | 8 | 4.8593 |
58
+ | No log | 9.0 | 9 | 4.7531 |
59
+ | 7.5936 | 10.0 | 10 | 4.6567 |
60
+ | 7.5936 | 11.0 | 11 | 4.5665 |
61
+ | 7.5936 | 12.0 | 12 | 4.4855 |
62
+ | 7.5936 | 13.0 | 13 | 4.4136 |
63
+ | 7.5936 | 14.0 | 14 | 4.3493 |
64
+ | 7.5936 | 15.0 | 15 | 4.2948 |
65
+ | 7.5936 | 16.0 | 16 | 4.2349 |
66
+ | 7.5936 | 17.0 | 17 | 4.1873 |
67
+ | 7.5936 | 18.0 | 18 | 4.1453 |
68
+ | 7.5936 | 19.0 | 19 | 4.1053 |
69
+ | 4.8063 | 20.0 | 20 | 4.0702 |
70
+ | 4.8063 | 21.0 | 21 | 4.0381 |
71
+ | 4.8063 | 22.0 | 22 | 4.0083 |
72
+ | 4.8063 | 23.0 | 23 | 3.9815 |
73
+ | 4.8063 | 24.0 | 24 | 3.9561 |
74
+ | 4.8063 | 25.0 | 25 | 3.9328 |
75
+ | 4.8063 | 26.0 | 26 | 3.9106 |
76
+ | 4.8063 | 27.0 | 27 | 3.8903 |
77
+ | 4.8063 | 28.0 | 28 | 3.8713 |
78
+ | 4.8063 | 29.0 | 29 | 3.8533 |
79
+ | 4.2429 | 30.0 | 30 | 3.8381 |
80
+ | 4.2429 | 31.0 | 31 | 3.8211 |
81
+ | 4.2429 | 32.0 | 32 | 3.8050 |
82
+ | 4.2429 | 33.0 | 33 | 3.7900 |
83
+ | 4.2429 | 34.0 | 34 | 3.7766 |
84
+ | 4.2429 | 35.0 | 35 | 3.7637 |
85
+ | 4.2429 | 36.0 | 36 | 3.7525 |
86
+ | 4.2429 | 37.0 | 37 | 3.7417 |
87
+ | 4.2429 | 38.0 | 38 | 3.7316 |
88
+ | 4.2429 | 39.0 | 39 | 3.7216 |
89
+ | 3.8807 | 40.0 | 40 | 3.7125 |
90
+ | 3.8807 | 41.0 | 41 | 3.7037 |
91
+ | 3.8807 | 42.0 | 42 | 3.6943 |
92
+ | 3.8807 | 43.0 | 43 | 3.6849 |
93
+ | 3.8807 | 44.0 | 44 | 3.6749 |
94
+ | 3.8807 | 45.0 | 45 | 3.6648 |
95
+ | 3.8807 | 46.0 | 46 | 3.6552 |
96
+ | 3.8807 | 47.0 | 47 | 3.6460 |
97
+ | 3.8807 | 48.0 | 48 | 3.6375 |
98
+ | 3.8807 | 49.0 | 49 | 3.6288 |
99
+ | 3.5855 | 50.0 | 50 | 3.6208 |
100
+ | 3.5855 | 51.0 | 51 | 3.6138 |
101
+ | 3.5855 | 52.0 | 52 | 3.6058 |
102
+ | 3.5855 | 53.0 | 53 | 3.5975 |
103
+ | 3.5855 | 54.0 | 54 | 3.5892 |
104
+ | 3.5855 | 55.0 | 55 | 3.5813 |
105
+ | 3.5855 | 56.0 | 56 | 3.5744 |
106
+ | 3.5855 | 57.0 | 57 | 3.5670 |
107
+ | 3.5855 | 58.0 | 58 | 3.5601 |
108
+ | 3.5855 | 59.0 | 59 | 3.5535 |
109
+ | 3.3324 | 60.0 | 60 | 3.5471 |
110
+ | 3.3324 | 61.0 | 61 | 3.5413 |
111
+ | 3.3324 | 62.0 | 62 | 3.5353 |
112
+ | 3.3324 | 63.0 | 63 | 3.5283 |
113
+ | 3.3324 | 64.0 | 64 | 3.5215 |
114
+ | 3.3324 | 65.0 | 65 | 3.5143 |
115
+ | 3.3324 | 66.0 | 66 | 3.5076 |
116
+ | 3.3324 | 67.0 | 67 | 3.5009 |
117
+ | 3.3324 | 68.0 | 68 | 3.4944 |
118
+ | 3.3324 | 69.0 | 69 | 3.4880 |
119
+ | 3.1425 | 70.0 | 70 | 3.4813 |
120
+ | 3.1425 | 71.0 | 71 | 3.4742 |
121
+ | 3.1425 | 72.0 | 72 | 3.4675 |
122
+ | 3.1425 | 73.0 | 73 | 3.4610 |
123
+ | 3.1425 | 74.0 | 74 | 3.4549 |
124
+ | 3.1425 | 75.0 | 75 | 3.4486 |
125
+ | 3.1425 | 76.0 | 76 | 3.4428 |
126
+ | 3.1425 | 77.0 | 77 | 3.4379 |
127
+ | 3.1425 | 78.0 | 78 | 3.4331 |
128
+ | 3.1425 | 79.0 | 79 | 3.4288 |
129
+ | 2.9782 | 80.0 | 80 | 3.4253 |
130
+ | 2.9782 | 81.0 | 81 | 3.4224 |
131
+ | 2.9782 | 82.0 | 82 | 3.4200 |
132
+ | 2.9782 | 83.0 | 83 | 3.4179 |
133
+ | 2.9782 | 84.0 | 84 | 3.4163 |
134
+ | 2.9782 | 85.0 | 85 | 3.4147 |
135
+ | 2.9782 | 86.0 | 86 | 3.4137 |
136
+ | 2.9782 | 87.0 | 87 | 3.4127 |
137
+ | 2.9782 | 88.0 | 88 | 3.4118 |
138
+ | 2.9782 | 89.0 | 89 | 3.4112 |
139
+ | 2.834 | 90.0 | 90 | 3.4107 |
140
+ | 2.834 | 91.0 | 91 | 3.4100 |
141
+ | 2.834 | 92.0 | 92 | 3.4089 |
142
+ | 2.834 | 93.0 | 93 | 3.4075 |
143
+ | 2.834 | 94.0 | 94 | 3.4058 |
144
+ | 2.834 | 95.0 | 95 | 3.4035 |
145
+ | 2.834 | 96.0 | 96 | 3.4022 |
146
+ | 2.834 | 97.0 | 97 | 3.4008 |
147
+ | 2.834 | 98.0 | 98 | 3.3992 |
148
+ | 2.834 | 99.0 | 99 | 3.3979 |
149
+ | 2.7066 | 100.0 | 100 | 3.3958 |
150
+ | 2.7066 | 101.0 | 101 | 3.3932 |
151
+ | 2.7066 | 102.0 | 102 | 3.3910 |
152
+ | 2.7066 | 103.0 | 103 | 3.3891 |
153
+ | 2.7066 | 104.0 | 104 | 3.3874 |
154
+ | 2.7066 | 105.0 | 105 | 3.3860 |
155
+ | 2.7066 | 106.0 | 106 | 3.3848 |
156
+ | 2.7066 | 107.0 | 107 | 3.3835 |
157
+ | 2.7066 | 108.0 | 108 | 3.3827 |
158
+ | 2.7066 | 109.0 | 109 | 3.3822 |
159
+ | 2.5945 | 110.0 | 110 | 3.3819 |
160
+ | 2.5945 | 111.0 | 111 | 3.3817 |
161
+ | 2.5945 | 112.0 | 112 | 3.3815 |
162
+ | 2.5945 | 113.0 | 113 | 3.3812 |
163
+ | 2.5945 | 114.0 | 114 | 3.3817 |
164
+ | 2.5945 | 115.0 | 115 | 3.3821 |
165
+ | 2.5945 | 116.0 | 116 | 3.3822 |
166
+ | 2.5945 | 117.0 | 117 | 3.3825 |
167
+ | 2.5945 | 118.0 | 118 | 3.3828 |
168
+ | 2.5945 | 119.0 | 119 | 3.3828 |
169
+ | 2.4939 | 120.0 | 120 | 3.3821 |
170
+ | 2.4939 | 121.0 | 121 | 3.3820 |
171
+ | 2.4939 | 122.0 | 122 | 3.3828 |
172
+ | 2.4939 | 123.0 | 123 | 3.3832 |
173
+ | 2.4939 | 124.0 | 124 | 3.3840 |
174
+ | 2.4939 | 125.0 | 125 | 3.3849 |
175
+ | 2.4939 | 126.0 | 126 | 3.3856 |
176
+ | 2.4939 | 127.0 | 127 | 3.3864 |
177
+ | 2.4939 | 128.0 | 128 | 3.3871 |
178
+ | 2.4939 | 129.0 | 129 | 3.3883 |
179
+ | 2.3964 | 130.0 | 130 | 3.3888 |
180
+ | 2.3964 | 131.0 | 131 | 3.3891 |
181
+ | 2.3964 | 132.0 | 132 | 3.3894 |
182
+ | 2.3964 | 133.0 | 133 | 3.3896 |
183
+ | 2.3964 | 134.0 | 134 | 3.3899 |
184
+ | 2.3964 | 135.0 | 135 | 3.3895 |
185
+ | 2.3964 | 136.0 | 136 | 3.3888 |
186
+ | 2.3964 | 137.0 | 137 | 3.3878 |
187
+ | 2.3964 | 138.0 | 138 | 3.3870 |
188
+ | 2.3964 | 139.0 | 139 | 3.3872 |
189
+ | 2.3127 | 140.0 | 140 | 3.3865 |
190
+ | 2.3127 | 141.0 | 141 | 3.3871 |
191
+ | 2.3127 | 142.0 | 142 | 3.3875 |
192
+ | 2.3127 | 143.0 | 143 | 3.3879 |
193
+ | 2.3127 | 144.0 | 144 | 3.3873 |
194
+ | 2.3127 | 145.0 | 145 | 3.3871 |
195
+ | 2.3127 | 146.0 | 146 | 3.3866 |
196
+ | 2.3127 | 147.0 | 147 | 3.3863 |
197
+ | 2.3127 | 148.0 | 148 | 3.3858 |
198
+ | 2.3127 | 149.0 | 149 | 3.3848 |
199
+ | 2.2501 | 150.0 | 150 | 3.3838 |
200
+ | 2.2501 | 151.0 | 151 | 3.3830 |
201
+ | 2.2501 | 152.0 | 152 | 3.3818 |
202
+ | 2.2501 | 153.0 | 153 | 3.3806 |
203
+ | 2.2501 | 154.0 | 154 | 3.3791 |
204
+ | 2.2501 | 155.0 | 155 | 3.3776 |
205
+ | 2.2501 | 156.0 | 156 | 3.3766 |
206
+ | 2.2501 | 157.0 | 157 | 3.3766 |
207
+ | 2.2501 | 158.0 | 158 | 3.3770 |
208
+ | 2.2501 | 159.0 | 159 | 3.3787 |
209
+ | 2.1825 | 160.0 | 160 | 3.3804 |
210
+ | 2.1825 | 161.0 | 161 | 3.3818 |
211
+ | 2.1825 | 162.0 | 162 | 3.3829 |
212
+ | 2.1825 | 163.0 | 163 | 3.3840 |
213
+ | 2.1825 | 164.0 | 164 | 3.3852 |
214
+ | 2.1825 | 165.0 | 165 | 3.3869 |
215
+ | 2.1825 | 166.0 | 166 | 3.3894 |
216
+ | 2.1825 | 167.0 | 167 | 3.3911 |
217
+ | 2.1825 | 168.0 | 168 | 3.3921 |
218
+ | 2.1825 | 169.0 | 169 | 3.3929 |
219
+ | 2.1136 | 170.0 | 170 | 3.3941 |
220
+ | 2.1136 | 171.0 | 171 | 3.3966 |
221
+ | 2.1136 | 172.0 | 172 | 3.3981 |
222
+ | 2.1136 | 173.0 | 173 | 3.3996 |
223
+ | 2.1136 | 174.0 | 174 | 3.4007 |
224
+ | 2.1136 | 175.0 | 175 | 3.4015 |
225
+ | 2.1136 | 176.0 | 176 | 3.4021 |
226
+ | 2.1136 | 177.0 | 177 | 3.4029 |
227
+ | 2.1136 | 178.0 | 178 | 3.4040 |
228
+ | 2.1136 | 179.0 | 179 | 3.4045 |
229
+ | 2.0567 | 180.0 | 180 | 3.4059 |
230
+ | 2.0567 | 181.0 | 181 | 3.4072 |
231
+ | 2.0567 | 182.0 | 182 | 3.4080 |
232
+ | 2.0567 | 183.0 | 183 | 3.4094 |
233
+ | 2.0567 | 184.0 | 184 | 3.4105 |
234
+ | 2.0567 | 185.0 | 185 | 3.4113 |
235
+ | 2.0567 | 186.0 | 186 | 3.4112 |
236
+ | 2.0567 | 187.0 | 187 | 3.4113 |
237
+ | 2.0567 | 188.0 | 188 | 3.4114 |
238
+ | 2.0567 | 189.0 | 189 | 3.4119 |
239
+ | 2.007 | 190.0 | 190 | 3.4131 |
240
+ | 2.007 | 191.0 | 191 | 3.4144 |
241
+ | 2.007 | 192.0 | 192 | 3.4153 |
242
+ | 2.007 | 193.0 | 193 | 3.4162 |
243
+ | 2.007 | 194.0 | 194 | 3.4169 |
244
+ | 2.007 | 195.0 | 195 | 3.4175 |
245
+ | 2.007 | 196.0 | 196 | 3.4183 |
246
+ | 2.007 | 197.0 | 197 | 3.4192 |
247
+ | 2.007 | 198.0 | 198 | 3.4202 |
248
+ | 2.007 | 199.0 | 199 | 3.4214 |
249
+ | 1.979 | 200.0 | 200 | 3.4226 |
250
+ | 1.979 | 201.0 | 201 | 3.4239 |
251
+ | 1.979 | 202.0 | 202 | 3.4257 |
252
+ | 1.979 | 203.0 | 203 | 3.4281 |
253
+ | 1.979 | 204.0 | 204 | 3.4301 |
254
+ | 1.979 | 205.0 | 205 | 3.4319 |
255
+ | 1.979 | 206.0 | 206 | 3.4334 |
256
+ | 1.979 | 207.0 | 207 | 3.4349 |
257
+ | 1.979 | 208.0 | 208 | 3.4358 |
258
+ | 1.979 | 209.0 | 209 | 3.4371 |
259
+ | 1.9314 | 210.0 | 210 | 3.4383 |
260
+ | 1.9314 | 211.0 | 211 | 3.4397 |
261
+ | 1.9314 | 212.0 | 212 | 3.4410 |
262
+ | 1.9314 | 213.0 | 213 | 3.4422 |
263
+ | 1.9314 | 214.0 | 214 | 3.4437 |
264
+ | 1.9314 | 215.0 | 215 | 3.4450 |
265
+ | 1.9314 | 216.0 | 216 | 3.4459 |
266
+ | 1.9314 | 217.0 | 217 | 3.4466 |
267
+ | 1.9314 | 218.0 | 218 | 3.4474 |
268
+ | 1.9314 | 219.0 | 219 | 3.4478 |
269
+ | 1.8941 | 220.0 | 220 | 3.4482 |
270
+ | 1.8941 | 221.0 | 221 | 3.4492 |
271
+ | 1.8941 | 222.0 | 222 | 3.4494 |
272
+ | 1.8941 | 223.0 | 223 | 3.4498 |
273
+ | 1.8941 | 224.0 | 224 | 3.4510 |
274
+ | 1.8941 | 225.0 | 225 | 3.4522 |
275
+ | 1.8941 | 226.0 | 226 | 3.4526 |
276
+ | 1.8941 | 227.0 | 227 | 3.4531 |
277
+ | 1.8941 | 228.0 | 228 | 3.4534 |
278
+ | 1.8941 | 229.0 | 229 | 3.4538 |
279
+ | 1.8591 | 230.0 | 230 | 3.4538 |
280
+ | 1.8591 | 231.0 | 231 | 3.4538 |
281
+ | 1.8591 | 232.0 | 232 | 3.4536 |
282
+ | 1.8591 | 233.0 | 233 | 3.4533 |
283
+ | 1.8591 | 234.0 | 234 | 3.4531 |
284
+ | 1.8591 | 235.0 | 235 | 3.4529 |
285
+ | 1.8591 | 236.0 | 236 | 3.4526 |
286
+ | 1.8591 | 237.0 | 237 | 3.4524 |
287
+ | 1.8591 | 238.0 | 238 | 3.4519 |
288
+ | 1.8591 | 239.0 | 239 | 3.4518 |
289
+ | 1.8297 | 240.0 | 240 | 3.4521 |
290
+ | 1.8297 | 241.0 | 241 | 3.4523 |
291
+ | 1.8297 | 242.0 | 242 | 3.4528 |
292
+ | 1.8297 | 243.0 | 243 | 3.4536 |
293
+ | 1.8297 | 244.0 | 244 | 3.4547 |
294
+ | 1.8297 | 245.0 | 245 | 3.4566 |
295
+ | 1.8297 | 246.0 | 246 | 3.4581 |
296
+ | 1.8297 | 247.0 | 247 | 3.4594 |
297
+ | 1.8297 | 248.0 | 248 | 3.4606 |
298
+ | 1.8297 | 249.0 | 249 | 3.4623 |
299
+ | 1.8027 | 250.0 | 250 | 3.4641 |
300
+ | 1.8027 | 251.0 | 251 | 3.4659 |
301
+ | 1.8027 | 252.0 | 252 | 3.4678 |
302
+ | 1.8027 | 253.0 | 253 | 3.4696 |
303
+ | 1.8027 | 254.0 | 254 | 3.4714 |
304
+ | 1.8027 | 255.0 | 255 | 3.4732 |
305
+ | 1.8027 | 256.0 | 256 | 3.4747 |
306
+ | 1.8027 | 257.0 | 257 | 3.4762 |
307
+ | 1.8027 | 258.0 | 258 | 3.4776 |
308
+ | 1.8027 | 259.0 | 259 | 3.4789 |
309
+ | 1.7679 | 260.0 | 260 | 3.4801 |
310
+ | 1.7679 | 261.0 | 261 | 3.4812 |
311
+ | 1.7679 | 262.0 | 262 | 3.4818 |
312
+ | 1.7679 | 263.0 | 263 | 3.4826 |
313
+ | 1.7679 | 264.0 | 264 | 3.4835 |
314
+ | 1.7679 | 265.0 | 265 | 3.4846 |
315
+ | 1.7679 | 266.0 | 266 | 3.4854 |
316
+ | 1.7679 | 267.0 | 267 | 3.4860 |
317
+ | 1.7679 | 268.0 | 268 | 3.4868 |
318
+ | 1.7679 | 269.0 | 269 | 3.4879 |
319
+ | 1.7506 | 270.0 | 270 | 3.4889 |
320
+ | 1.7506 | 271.0 | 271 | 3.4901 |
321
+ | 1.7506 | 272.0 | 272 | 3.4909 |
322
+ | 1.7506 | 273.0 | 273 | 3.4913 |
323
+ | 1.7506 | 274.0 | 274 | 3.4921 |
324
+ | 1.7506 | 275.0 | 275 | 3.4931 |
325
+ | 1.7506 | 276.0 | 276 | 3.4938 |
326
+ | 1.7506 | 277.0 | 277 | 3.4942 |
327
+ | 1.7506 | 278.0 | 278 | 3.4945 |
328
+ | 1.7506 | 279.0 | 279 | 3.4949 |
329
+ | 1.7302 | 280.0 | 280 | 3.4958 |
330
+ | 1.7302 | 281.0 | 281 | 3.4970 |
331
+ | 1.7302 | 282.0 | 282 | 3.4979 |
332
+ | 1.7302 | 283.0 | 283 | 3.4983 |
333
+ | 1.7302 | 284.0 | 284 | 3.4984 |
334
+ | 1.7302 | 285.0 | 285 | 3.4983 |
335
+ | 1.7302 | 286.0 | 286 | 3.4982 |
336
+ | 1.7302 | 287.0 | 287 | 3.4983 |
337
+ | 1.7302 | 288.0 | 288 | 3.4982 |
338
+ | 1.7302 | 289.0 | 289 | 3.4979 |
339
+ | 1.705 | 290.0 | 290 | 3.4973 |
340
+ | 1.705 | 291.0 | 291 | 3.4972 |
341
+ | 1.705 | 292.0 | 292 | 3.4970 |
342
+ | 1.705 | 293.0 | 293 | 3.4970 |
343
+ | 1.705 | 294.0 | 294 | 3.4972 |
344
+ | 1.705 | 295.0 | 295 | 3.4978 |
345
+ | 1.705 | 296.0 | 296 | 3.4983 |
346
+ | 1.705 | 297.0 | 297 | 3.4990 |
347
+ | 1.705 | 298.0 | 298 | 3.4997 |
348
+ | 1.705 | 299.0 | 299 | 3.5001 |
349
+ | 1.6943 | 300.0 | 300 | 3.5006 |
350
+ | 1.6943 | 301.0 | 301 | 3.5012 |
351
+ | 1.6943 | 302.0 | 302 | 3.5019 |
352
+ | 1.6943 | 303.0 | 303 | 3.5031 |
353
+ | 1.6943 | 304.0 | 304 | 3.5042 |
354
+ | 1.6943 | 305.0 | 305 | 3.5058 |
355
+ | 1.6943 | 306.0 | 306 | 3.5072 |
356
+ | 1.6943 | 307.0 | 307 | 3.5072 |
357
+ | 1.6943 | 308.0 | 308 | 3.5082 |
358
+ | 1.6943 | 309.0 | 309 | 3.5097 |
359
+ | 1.6733 | 310.0 | 310 | 3.5113 |
360
+ | 1.6733 | 311.0 | 311 | 3.5129 |
361
+ | 1.6733 | 312.0 | 312 | 3.5142 |
362
+ | 1.6733 | 313.0 | 313 | 3.5157 |
363
+ | 1.6733 | 314.0 | 314 | 3.5174 |
364
+ | 1.6733 | 315.0 | 315 | 3.5203 |
365
+ | 1.6733 | 316.0 | 316 | 3.5221 |
366
+ | 1.6733 | 317.0 | 317 | 3.5230 |
367
+ | 1.6733 | 318.0 | 318 | 3.5239 |
368
+ | 1.6733 | 319.0 | 319 | 3.5245 |
369
+ | 1.6582 | 320.0 | 320 | 3.5250 |
370
+ | 1.6582 | 321.0 | 321 | 3.5254 |
371
+ | 1.6582 | 322.0 | 322 | 3.5259 |
372
+ | 1.6582 | 323.0 | 323 | 3.5263 |
373
+ | 1.6582 | 324.0 | 324 | 3.5266 |
374
+ | 1.6582 | 325.0 | 325 | 3.5270 |
375
+ | 1.6582 | 326.0 | 326 | 3.5274 |
376
+ | 1.6582 | 327.0 | 327 | 3.5278 |
377
+ | 1.6582 | 328.0 | 328 | 3.5281 |
378
+ | 1.6582 | 329.0 | 329 | 3.5284 |
379
+ | 1.6567 | 330.0 | 330 | 3.5287 |
380
+ | 1.6567 | 331.0 | 331 | 3.5290 |
381
+ | 1.6567 | 332.0 | 332 | 3.5295 |
382
+ | 1.6567 | 333.0 | 333 | 3.5300 |
383
+ | 1.6567 | 334.0 | 334 | 3.5303 |
384
+ | 1.6567 | 335.0 | 335 | 3.5309 |
385
+ | 1.6567 | 336.0 | 336 | 3.5315 |
386
+ | 1.6567 | 337.0 | 337 | 3.5323 |
387
+ | 1.6567 | 338.0 | 338 | 3.5330 |
388
+ | 1.6567 | 339.0 | 339 | 3.5336 |
389
+ | 1.6443 | 340.0 | 340 | 3.5340 |
390
+ | 1.6443 | 341.0 | 341 | 3.5344 |
391
+ | 1.6443 | 342.0 | 342 | 3.5346 |
392
+ | 1.6443 | 343.0 | 343 | 3.5347 |
393
+ | 1.6443 | 344.0 | 344 | 3.5350 |
394
+ | 1.6443 | 345.0 | 345 | 3.5352 |
395
+ | 1.6443 | 346.0 | 346 | 3.5355 |
396
+ | 1.6443 | 347.0 | 347 | 3.5357 |
397
+ | 1.6443 | 348.0 | 348 | 3.5358 |
398
+ | 1.6443 | 349.0 | 349 | 3.5359 |
399
+ | 1.6377 | 350.0 | 350 | 3.5361 |
400
+ | 1.6377 | 351.0 | 351 | 3.5362 |
401
+ | 1.6377 | 352.0 | 352 | 3.5363 |
402
+ | 1.6377 | 353.0 | 353 | 3.5364 |
403
+ | 1.6377 | 354.0 | 354 | 3.5366 |
404
+ | 1.6377 | 355.0 | 355 | 3.5369 |
405
+ | 1.6377 | 356.0 | 356 | 3.5371 |
406
+ | 1.6377 | 357.0 | 357 | 3.5373 |
407
+ | 1.6377 | 358.0 | 358 | 3.5374 |
408
+ | 1.6377 | 359.0 | 359 | 3.5376 |
409
+ | 1.6246 | 360.0 | 360 | 3.5377 |
410
+ | 1.6246 | 361.0 | 361 | 3.5378 |
411
+ | 1.6246 | 362.0 | 362 | 3.5378 |
412
+ | 1.6246 | 363.0 | 363 | 3.5379 |
413
+ | 1.6246 | 364.0 | 364 | 3.5381 |
414
+ | 1.6246 | 365.0 | 365 | 3.5382 |
415
+ | 1.6246 | 366.0 | 366 | 3.5383 |
416
+ | 1.6246 | 367.0 | 367 | 3.5384 |
417
+ | 1.6246 | 368.0 | 368 | 3.5385 |
418
+ | 1.6246 | 369.0 | 369 | 3.5386 |
419
+ | 1.6327 | 370.0 | 370 | 3.5386 |
420
+ | 1.6327 | 371.0 | 371 | 3.5387 |
421
+ | 1.6327 | 372.0 | 372 | 3.5387 |
422
+ | 1.6327 | 373.0 | 373 | 3.5388 |
423
+ | 1.6327 | 374.0 | 374 | 3.5388 |
424
+ | 1.6327 | 375.0 | 375 | 3.5388 |
425
+
426
+
427
+ ### Framework versions
428
+
429
+ - Transformers 4.49.0
430
+ - Pytorch 2.6.0+cu124
431
+ - Datasets 3.4.1
432
+ - Tokenizers 0.21.1
generation_config.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "decoder_start_token_id": 0,
4
+ "eos_token_id": 1,
5
+ "pad_token_id": 0,
6
+ "transformers_version": "4.49.0"
7
+ }