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t5-text2sql

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t5
text2text-generation
Generated from Trainer
text-generation-inference
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update model card README.md

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@@ -13,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1307
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- - Rouge2 Precision: 0.9107
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- - Rouge2 Recall: 0.2699
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- - Rouge2 Fmeasure: 0.3853
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  ## Model description
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@@ -41,62 +41,42 @@ The following hyperparameters were used during training:
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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
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- - num_epochs: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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- | No log | 1.0 | 11 | 0.1513 | 0.9127 | 0.2859 | 0.4019 |
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- | No log | 2.0 | 22 | 0.1223 | 0.8532 | 0.2632 | 0.369 |
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- | No log | 3.0 | 33 | 0.1378 | 0.8948 | 0.2684 | 0.3816 |
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- | No log | 4.0 | 44 | 0.1218 | 0.9067 | 0.2692 | 0.3844 |
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- | No log | 5.0 | 55 | 0.1331 | 0.9048 | 0.2684 | 0.3835 |
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- | No log | 6.0 | 66 | 0.1265 | 0.8948 | 0.2667 | 0.3796 |
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- | No log | 7.0 | 77 | 0.1300 | 0.9127 | 0.2865 | 0.4003 |
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- | No log | 8.0 | 88 | 0.1317 | 0.8835 | 0.2623 | 0.3729 |
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- | No log | 9.0 | 99 | 0.1313 | 0.9008 | 0.2679 | 0.3815 |
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- | No log | 10.0 | 110 | 0.1253 | 0.9008 | 0.2679 | 0.3815 |
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- | No log | 11.0 | 121 | 0.1277 | 0.9048 | 0.2685 | 0.3829 |
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- | No log | 12.0 | 132 | 0.1275 | 0.8988 | 0.2673 | 0.3809 |
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- | No log | 13.0 | 143 | 0.1226 | 0.8829 | 0.2636 | 0.3746 |
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- | No log | 14.0 | 154 | 0.1254 | 0.8948 | 0.2667 | 0.3796 |
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- | No log | 15.0 | 165 | 0.1332 | 0.9048 | 0.2684 | 0.3835 |
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- | No log | 16.0 | 176 | 0.1219 | 0.8821 | 0.2625 | 0.3733 |
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- | No log | 17.0 | 187 | 0.1274 | 0.8988 | 0.2673 | 0.3809 |
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- | No log | 18.0 | 198 | 0.1328 | 0.8948 | 0.2667 | 0.3796 |
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- | No log | 19.0 | 209 | 0.1315 | 0.8948 | 0.2667 | 0.3796 |
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- | No log | 20.0 | 220 | 0.1259 | 0.8948 | 0.2667 | 0.3796 |
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- | No log | 21.0 | 231 | 0.1298 | 0.8948 | 0.2667 | 0.3796 |
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- | No log | 22.0 | 242 | 0.1268 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 23.0 | 253 | 0.1287 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 24.0 | 264 | 0.1296 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 25.0 | 275 | 0.1220 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 26.0 | 286 | 0.1292 | 0.9107 | 0.2701 | 0.3859 |
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- | No log | 27.0 | 297 | 0.1296 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 28.0 | 308 | 0.1270 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 29.0 | 319 | 0.1233 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 30.0 | 330 | 0.1247 | 0.9048 | 0.2684 | 0.3835 |
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- | No log | 31.0 | 341 | 0.1209 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 32.0 | 352 | 0.1236 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 33.0 | 363 | 0.1312 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 34.0 | 374 | 0.1340 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 35.0 | 385 | 0.1237 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 36.0 | 396 | 0.1234 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 37.0 | 407 | 0.1255 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 38.0 | 418 | 0.1274 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 39.0 | 429 | 0.1270 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 40.0 | 440 | 0.1263 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 41.0 | 451 | 0.1274 | 0.9028 | 0.2685 | 0.3821 |
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- | No log | 42.0 | 462 | 0.1267 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 43.0 | 473 | 0.1287 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 44.0 | 484 | 0.1312 | 0.9107 | 0.2699 | 0.3853 |
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- | No log | 45.0 | 495 | 0.1314 | 0.9107 | 0.2699 | 0.3853 |
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- | 0.0146 | 46.0 | 506 | 0.1317 | 0.9107 | 0.2699 | 0.3853 |
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- | 0.0146 | 47.0 | 517 | 0.1314 | 0.9107 | 0.2699 | 0.3853 |
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- | 0.0146 | 48.0 | 528 | 0.1313 | 0.9107 | 0.2699 | 0.3853 |
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- | 0.0146 | 49.0 | 539 | 0.1308 | 0.9107 | 0.2699 | 0.3853 |
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- | 0.0146 | 50.0 | 550 | 0.1307 | 0.9107 | 0.2699 | 0.3853 |
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  ### Framework versions
 
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  This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1337
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+ - Rouge2 Precision: 0.9067
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+ - Rouge2 Recall: 0.2721
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+ - Rouge2 Fmeasure: 0.3864
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  ## Model description
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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
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+ - num_epochs: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | No log | 1.0 | 11 | 0.1491 | 0.9028 | 0.2685 | 0.3821 |
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+ | No log | 2.0 | 22 | 0.1412 | 0.881 | 0.2636 | 0.3736 |
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+ | No log | 3.0 | 33 | 0.1278 | 0.8651 | 0.2591 | 0.3667 |
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+ | No log | 4.0 | 44 | 0.1260 | 0.8324 | 0.2421 | 0.3449 |
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+ | No log | 5.0 | 55 | 0.1383 | 0.8611 | 0.251 | 0.3588 |
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+ | No log | 6.0 | 66 | 0.1437 | 0.9028 | 0.2685 | 0.3821 |
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+ | No log | 7.0 | 77 | 0.1435 | 0.881 | 0.2633 | 0.3731 |
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+ | No log | 8.0 | 88 | 0.1402 | 0.881 | 0.2633 | 0.3731 |
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+ | No log | 9.0 | 99 | 0.1292 | 0.9028 | 0.2685 | 0.3821 |
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+ | No log | 10.0 | 110 | 0.1324 | 0.9028 | 0.2685 | 0.3821 |
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+ | No log | 11.0 | 121 | 0.1518 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 12.0 | 132 | 0.1368 | 0.9028 | 0.2708 | 0.3836 |
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+ | No log | 13.0 | 143 | 0.1333 | 0.9028 | 0.2708 | 0.3836 |
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+ | No log | 14.0 | 154 | 0.1359 | 0.8988 | 0.2675 | 0.38 |
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+ | No log | 15.0 | 165 | 0.1415 | 0.9028 | 0.2708 | 0.3836 |
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+ | No log | 16.0 | 176 | 0.1397 | 0.9028 | 0.2708 | 0.3836 |
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+ | No log | 17.0 | 187 | 0.1415 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 18.0 | 198 | 0.1339 | 0.9147 | 0.2731 | 0.3889 |
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+ | No log | 19.0 | 209 | 0.1345 | 0.9147 | 0.2731 | 0.3889 |
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+ | No log | 20.0 | 220 | 0.1371 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 21.0 | 231 | 0.1368 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 22.0 | 242 | 0.1342 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 23.0 | 253 | 0.1331 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 24.0 | 264 | 0.1335 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 25.0 | 275 | 0.1343 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 26.0 | 286 | 0.1348 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 27.0 | 297 | 0.1345 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 28.0 | 308 | 0.1343 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 29.0 | 319 | 0.1338 | 0.9067 | 0.2721 | 0.3864 |
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+ | No log | 30.0 | 330 | 0.1337 | 0.9067 | 0.2721 | 0.3864 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions