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irp1999
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mbart-neutralization

Transformers
TensorBoard
Safetensors
mbart
text2text-generation
simplification
Generated from Trainer
Model card Files
xet
Metrics Community
irp1999 commited on
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Training complete

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Files changed (10) hide show
  1. README.md +13 -13
  2. config.json +52 -48
  3. generation_config.json +3 -8
  4. model.safetensors +2 -2
  5. runs/Feb18_20-53-04_f1642f2791d0/events.out.tfevents.1708289620.f1642f2791d0.1156.0 +3 -0
  6. special_tokens_map.json +118 -62
  7. spiece.model +3 -0
  8. tokenizer.json +2 -2
  9. tokenizer_config.json +584 -173
  10. training_args.bin +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
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- license: mit
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- base_model: facebook/mbart-large-50
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  tags:
5
  - simplification
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  - generated_from_trainer
@@ -16,11 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # mbart-neutralization
18
 
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- This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.5140
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- - Bleu: 10.6012
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- - Gen Len: 21.5854
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  ## Model description
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@@ -40,8 +40,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -49,10 +49,10 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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- | No log | 1.0 | 16 | 3.7443 | 7.8006 | 18.3171 |
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- | No log | 2.0 | 32 | 3.5140 | 10.6012 | 21.5854 |
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  ### Framework versions
@@ -60,4 +60,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.0
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- - Tokenizers 0.15.1
 
1
  ---
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+ license: apache-2.0
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+ base_model: google/flan-t5-base
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  tags:
5
  - simplification
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  - generated_from_trainer
 
16
 
17
  # mbart-neutralization
18
 
19
+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 1.3981
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+ - Bleu: 0.8291
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+ - Gen Len: 19.0
24
 
25
  ## Model description
26
 
 
40
 
41
  The following hyperparameters were used during training:
42
  - learning_rate: 5.6e-05
43
+ - train_batch_size: 1
44
+ - eval_batch_size: 1
45
  - seed: 42
46
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
  - lr_scheduler_type: linear
 
49
 
50
  ### Training results
51
 
52
+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
53
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | No log | 1.0 | 121 | 1.4544 | 0.9156 | 19.0 |
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+ | No log | 2.0 | 242 | 1.3981 | 0.8291 | 19.0 |
56
 
57
 
58
  ### Framework versions
 
60
  - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.0
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+ - Tokenizers 0.15.2
config.json CHANGED
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110
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111
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112
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113
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114
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115
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116
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117
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118
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119
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120
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121
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122
  },
123
- "250012": {
124
- "content": "ja_XX",
125
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126
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127
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128
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129
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130
  },
131
- "250013": {
132
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133
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134
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135
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136
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137
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138
  },
139
- "250014": {
140
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141
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142
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143
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144
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145
  "special": true
146
  },
147
- "250015": {
148
- "content": "lt_LT",
149
  "lstrip": false,
150
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151
  "rstrip": false,
152
  "single_word": false,
153
  "special": true
154
  },
155
- "250016": {
156
- "content": "lv_LV",
157
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158
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159
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160
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161
  "special": true
162
  },
163
- "250017": {
164
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165
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166
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167
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168
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169
  "special": true
170
  },
171
- "250018": {
172
- "content": "ne_NP",
173
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174
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175
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176
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177
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178
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179
- "250019": {
180
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181
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182
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183
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184
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185
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186
  },
187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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197
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198
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199
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200
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201
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202
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203
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204
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205
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206
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207
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208
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209
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210
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211
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212
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213
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214
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215
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216
  "single_word": false,
217
  "special": true
218
  },
219
- "250024": {
220
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221
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222
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223
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224
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225
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226
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227
- "250025": {
228
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229
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230
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231
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232
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233
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234
  },
235
- "250026": {
236
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237
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238
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239
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240
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241
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242
  },
243
- "250027": {
244
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245
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246
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247
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248
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249
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250
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251
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252
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253
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254
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255
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256
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257
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258
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259
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260
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261
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262
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263
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264
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265
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266
  },
267
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268
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269
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270
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271
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272
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273
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274
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275
- "250031": {
276
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277
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278
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279
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280
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281
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282
  },
283
- "250032": {
284
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285
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286
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287
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288
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289
  "special": true
290
  },
291
- "250033": {
292
- "content": "ka_GE",
293
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294
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295
  "rstrip": false,
296
  "single_word": false,
297
  "special": true
298
  },
299
- "250034": {
300
- "content": "km_KH",
301
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302
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303
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304
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305
  "special": true
306
  },
307
- "250035": {
308
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309
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310
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311
  "rstrip": false,
312
  "single_word": false,
313
  "special": true
314
  },
315
- "250036": {
316
- "content": "ml_IN",
317
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318
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319
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320
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321
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322
  },
323
- "250037": {
324
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325
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326
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327
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328
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329
  "special": true
330
  },
331
- "250038": {
332
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333
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334
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335
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336
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337
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338
  },
339
- "250039": {
340
- "content": "pl_PL",
341
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342
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343
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344
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345
  "special": true
346
  },
347
- "250040": {
348
- "content": "ps_AF",
349
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350
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351
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352
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353
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354
  },
355
- "250041": {
356
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357
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358
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359
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360
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361
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362
  },
363
- "250042": {
364
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365
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366
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367
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368
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369
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370
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371
- "250043": {
372
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373
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374
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375
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376
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377
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378
  },
379
- "250044": {
380
- "content": "ta_IN",
381
  "lstrip": false,
382
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383
  "rstrip": false,
384
  "single_word": false,
385
  "special": true
386
  },
387
- "250045": {
388
- "content": "te_IN",
389
  "lstrip": false,
390
  "normalized": false,
391
  "rstrip": false,
392
  "single_word": false,
393
  "special": true
394
  },
395
- "250046": {
396
- "content": "th_TH",
397
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398
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399
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400
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401
  "special": true
402
  },
403
- "250047": {
404
- "content": "tl_XX",
405
  "lstrip": false,
406
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407
  "rstrip": false,
408
  "single_word": false,
409
  "special": true
410
  },
411
- "250048": {
412
- "content": "uk_UA",
413
  "lstrip": false,
414
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415
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416
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417
  "special": true
418
  },
419
- "250049": {
420
- "content": "ur_PK",
421
  "lstrip": false,
422
  "normalized": false,
423
  "rstrip": false,
424
  "single_word": false,
425
  "special": true
426
  },
427
- "250050": {
428
- "content": "xh_ZA",
429
  "lstrip": false,
430
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431
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432
  "single_word": false,
433
  "special": true
434
  },
435
- "250051": {
436
- "content": "gl_ES",
437
  "lstrip": false,
438
  "normalized": false,
439
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440
  "single_word": false,
441
  "special": true
442
  },
443
- "250052": {
444
- "content": "sl_SI",
445
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446
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447
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448
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449
  "special": true
450
  },
451
- "250053": {
452
- "content": "<mask>",
453
- "lstrip": true,
454
- "normalized": true,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
455
  "rstrip": false,
456
  "single_word": false,
457
  "special": true
458
  }
459
  },
460
  "additional_special_tokens": [
461
- "ar_AR",
462
- "cs_CZ",
463
- "de_DE",
464
- "en_XX",
465
- "es_XX",
466
- "et_EE",
467
- "fi_FI",
468
- "fr_XX",
469
- "gu_IN",
470
- "hi_IN",
471
- "it_IT",
472
- "ja_XX",
473
- "kk_KZ",
474
- "ko_KR",
475
- "lt_LT",
476
- "lv_LV",
477
- "my_MM",
478
- "ne_NP",
479
- "nl_XX",
480
- "ro_RO",
481
- "ru_RU",
482
- "si_LK",
483
- "tr_TR",
484
- "vi_VN",
485
- "zh_CN",
486
- "af_ZA",
487
- "az_AZ",
488
- "bn_IN",
489
- "fa_IR",
490
- "he_IL",
491
- "hr_HR",
492
- "id_ID",
493
- "ka_GE",
494
- "km_KH",
495
- "mk_MK",
496
- "ml_IN",
497
- "mn_MN",
498
- "mr_IN",
499
- "pl_PL",
500
- "ps_AF",
501
- "pt_XX",
502
- "sv_SE",
503
- "sw_KE",
504
- "ta_IN",
505
- "te_IN",
506
- "th_TH",
507
- "tl_XX",
508
- "uk_UA",
509
- "ur_PK",
510
- "xh_ZA",
511
- "gl_ES",
512
- "sl_SI"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
513
  ],
514
- "bos_token": "<s>",
515
  "clean_up_tokenization_spaces": true,
516
- "cls_token": "<s>",
517
  "eos_token": "</s>",
518
- "mask_token": "<mask>",
519
- "model_max_length": 1024,
520
  "pad_token": "<pad>",
521
- "sep_token": "</s>",
522
  "sp_model_kwargs": {},
523
- "src_lang": "en_XX",
524
- "tgt_lang": null,
525
- "tokenizer_class": "MBart50Tokenizer",
526
  "unk_token": "<unk>"
527
  }
 
1
  {
2
  "added_tokens_decoder": {
3
  "0": {
4
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5
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6
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7
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9
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10
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11
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12
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13
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14
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15
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17
  "special": true
18
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19
  "2": {
20
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21
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22
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26
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283
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285
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