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ms8080
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calculator_model_test_2

Transformers
Safetensors
encoder-decoder
text2text-generation
Generated from Trainer
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End of training

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  1. README.md +102 -42
README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4881
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  ## Model description
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@@ -39,53 +39,113 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 40
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 3.2172 | 1.0 | 14 | 2.4439 |
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- | 2.2511 | 2.0 | 28 | 2.0993 |
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- | 1.8900 | 3.0 | 42 | 1.6658 |
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- | 1.5938 | 4.0 | 56 | 1.5309 |
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- | 1.5062 | 5.0 | 70 | 1.4552 |
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- | 1.4073 | 6.0 | 84 | 1.3081 |
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- | 1.2474 | 7.0 | 98 | 1.1300 |
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- | 1.0879 | 8.0 | 112 | 1.0155 |
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- | 1.0071 | 9.0 | 126 | 0.9430 |
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- | 0.9353 | 10.0 | 140 | 0.8832 |
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- | 0.8847 | 11.0 | 154 | 0.8358 |
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- | 0.8417 | 12.0 | 168 | 0.7919 |
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- | 0.8073 | 13.0 | 182 | 0.7743 |
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- | 0.8013 | 14.0 | 196 | 0.8096 |
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- | 0.7776 | 15.0 | 210 | 0.7482 |
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- | 0.7476 | 16.0 | 224 | 0.7241 |
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- | 0.7231 | 17.0 | 238 | 0.7127 |
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- | 0.7045 | 18.0 | 252 | 0.6679 |
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- | 0.6851 | 19.0 | 266 | 0.6536 |
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- | 0.6707 | 20.0 | 280 | 0.6485 |
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- | 0.6507 | 21.0 | 294 | 0.6197 |
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- | 0.6447 | 22.0 | 308 | 0.6277 |
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- | 0.6359 | 23.0 | 322 | 0.6155 |
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- | 0.6184 | 24.0 | 336 | 0.6017 |
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- | 0.6143 | 25.0 | 350 | 0.5939 |
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- | 0.5941 | 26.0 | 364 | 0.5718 |
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- | 0.5859 | 27.0 | 378 | 0.5659 |
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- | 0.5741 | 28.0 | 392 | 0.5695 |
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- | 0.5714 | 29.0 | 406 | 0.5546 |
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- | 0.5585 | 30.0 | 420 | 0.5382 |
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- | 0.5445 | 31.0 | 434 | 0.5273 |
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- | 0.5361 | 32.0 | 448 | 0.5203 |
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- | 0.5292 | 33.0 | 462 | 0.5166 |
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- | 0.5218 | 34.0 | 476 | 0.5145 |
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- | 0.5153 | 35.0 | 490 | 0.5066 |
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- | 0.5098 | 36.0 | 504 | 0.4994 |
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- | 0.5039 | 37.0 | 518 | 0.4933 |
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- | 0.5011 | 38.0 | 532 | 0.4913 |
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- | 0.4962 | 39.0 | 546 | 0.4892 |
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- | 0.4929 | 40.0 | 560 | 0.4881 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0060
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 100
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.0266 | 1.0 | 6 | 2.2481 |
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+ | 2.0347 | 2.0 | 12 | 1.7403 |
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+ | 1.5575 | 3.0 | 18 | 1.3098 |
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+ | 1.2110 | 4.0 | 24 | 1.0916 |
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+ | 1.0460 | 5.0 | 30 | 0.9786 |
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+ | 0.9417 | 6.0 | 36 | 0.8630 |
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+ | 0.8312 | 7.0 | 42 | 0.7454 |
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+ | 0.7230 | 8.0 | 48 | 0.6662 |
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+ | 0.6606 | 9.0 | 54 | 0.6547 |
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+ | 0.6435 | 10.0 | 60 | 0.6063 |
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+ | 0.5876 | 11.0 | 66 | 0.5376 |
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+ | 0.5490 | 12.0 | 72 | 0.5449 |
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+ | 0.5356 | 13.0 | 78 | 0.4940 |
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+ | 0.5389 | 14.0 | 84 | 0.5342 |
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+ | 0.5251 | 15.0 | 90 | 0.4613 |
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+ | 0.4776 | 16.0 | 96 | 0.4339 |
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+ | 0.4445 | 17.0 | 102 | 0.4073 |
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+ | 0.4183 | 18.0 | 108 | 0.4256 |
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+ | 0.4132 | 19.0 | 114 | 0.3678 |
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+ | 0.3785 | 20.0 | 120 | 0.3386 |
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+ | 0.3393 | 21.0 | 126 | 0.3191 |
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+ | 0.3229 | 22.0 | 132 | 0.2889 |
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+ | 0.2948 | 23.0 | 138 | 0.2484 |
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+ | 0.2685 | 24.0 | 144 | 0.2395 |
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+ | 0.2560 | 25.0 | 150 | 0.2348 |
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+ | 0.2317 | 26.0 | 156 | 0.2351 |
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+ | 0.2329 | 27.0 | 162 | 0.2155 |
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+ | 0.2190 | 28.0 | 168 | 0.1862 |
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+ | 0.1964 | 29.0 | 174 | 0.1616 |
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+ | 0.1796 | 30.0 | 180 | 0.1456 |
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+ | 0.1560 | 31.0 | 186 | 0.1129 |
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+ | 0.1371 | 32.0 | 192 | 0.0992 |
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+ | 0.1370 | 33.0 | 198 | 0.0862 |
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+ | 0.1176 | 34.0 | 204 | 0.0849 |
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+ | 0.1088 | 35.0 | 210 | 0.0951 |
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+ | 0.1017 | 36.0 | 216 | 0.0656 |
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+ | 0.0873 | 37.0 | 222 | 0.0515 |
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+ | 0.0777 | 38.0 | 228 | 0.0761 |
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+ | 0.0915 | 39.0 | 234 | 0.0521 |
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+ | 0.0772 | 40.0 | 240 | 0.0500 |
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+ | 0.0705 | 41.0 | 246 | 0.0437 |
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+ | 0.0662 | 42.0 | 252 | 0.0470 |
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+ | 0.0629 | 43.0 | 258 | 0.0441 |
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+ | 0.0611 | 44.0 | 264 | 0.0364 |
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+ | 0.0587 | 45.0 | 270 | 0.0356 |
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+ | 0.0523 | 46.0 | 276 | 0.0315 |
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+ | 0.0464 | 47.0 | 282 | 0.0274 |
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+ | 0.0467 | 48.0 | 288 | 0.0289 |
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+ | 0.0444 | 49.0 | 294 | 0.0323 |
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+ | 0.0462 | 50.0 | 300 | 0.0259 |
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+ | 0.0381 | 51.0 | 306 | 0.0234 |
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+ | 0.0390 | 52.0 | 312 | 0.0251 |
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+ | 0.0373 | 53.0 | 318 | 0.0272 |
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+ | 0.0381 | 54.0 | 324 | 0.0223 |
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+ | 0.0358 | 55.0 | 330 | 0.0287 |
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+ | 0.0412 | 56.0 | 336 | 0.0252 |
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+ | 0.0391 | 57.0 | 342 | 0.0242 |
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+ | 0.0391 | 58.0 | 348 | 0.0207 |
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+ | 0.0354 | 59.0 | 354 | 0.0223 |
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+ | 0.0308 | 60.0 | 360 | 0.0190 |
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+ | 0.0290 | 61.0 | 366 | 0.0158 |
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+ | 0.0254 | 62.0 | 372 | 0.0139 |
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+ | 0.0231 | 63.0 | 378 | 0.0153 |
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+ | 0.0226 | 64.0 | 384 | 0.0135 |
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+ | 0.0240 | 65.0 | 390 | 0.0133 |
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+ | 0.0224 | 66.0 | 396 | 0.0147 |
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+ | 0.0196 | 67.0 | 402 | 0.0111 |
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+ | 0.0180 | 68.0 | 408 | 0.0119 |
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+ | 0.0169 | 69.0 | 414 | 0.0119 |
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+ | 0.0181 | 70.0 | 420 | 0.0109 |
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+ | 0.0161 | 71.0 | 426 | 0.0102 |
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+ | 0.0151 | 72.0 | 432 | 0.0100 |
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+ | 0.0139 | 73.0 | 438 | 0.0105 |
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+ | 0.0169 | 74.0 | 444 | 0.0088 |
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+ | 0.0124 | 75.0 | 450 | 0.0082 |
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+ | 0.0122 | 76.0 | 456 | 0.0083 |
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+ | 0.0125 | 77.0 | 462 | 0.0080 |
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+ | 0.0112 | 78.0 | 468 | 0.0084 |
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+ | 0.0109 | 79.0 | 474 | 0.0079 |
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+ | 0.0103 | 80.0 | 480 | 0.0076 |
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+ | 0.0103 | 81.0 | 486 | 0.0072 |
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+ | 0.0101 | 82.0 | 492 | 0.0069 |
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+ | 0.0091 | 83.0 | 498 | 0.0068 |
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+ | 0.0114 | 84.0 | 504 | 0.0068 |
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+ | 0.0108 | 85.0 | 510 | 0.0070 |
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+ | 0.0101 | 86.0 | 516 | 0.0066 |
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+ | 0.0132 | 87.0 | 522 | 0.0067 |
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+ | 0.0092 | 88.0 | 528 | 0.0070 |
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+ | 0.0103 | 89.0 | 534 | 0.0066 |
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+ | 0.0101 | 90.0 | 540 | 0.0064 |
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+ | 0.0088 | 91.0 | 546 | 0.0062 |
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+ | 0.0086 | 92.0 | 552 | 0.0062 |
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+ | 0.0085 | 93.0 | 558 | 0.0062 |
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+ | 0.0083 | 94.0 | 564 | 0.0062 |
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+ | 0.0086 | 95.0 | 570 | 0.0061 |
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+ | 0.0089 | 96.0 | 576 | 0.0061 |
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+ | 0.0091 | 97.0 | 582 | 0.0060 |
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+ | 0.0096 | 98.0 | 588 | 0.0060 |
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+ | 0.0103 | 99.0 | 594 | 0.0060 |
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+ | 0.0101 | 100.0 | 600 | 0.0060 |
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  ### Framework versions