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--- |
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license: apache-2.0 |
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base_model: google/mt5-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: cs_mT5-large2_2e-5_100_v0.4 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# cs_mT5-large2_2e-5_100_v0.4 |
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This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1297 |
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- Bleu: 12.9589 |
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- Gen Len: 15.7619 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 100 |
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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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| 18.9475 | 1.0 | 6 | 8.4357 | 8.3431 | 19.0 | |
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| 11.3295 | 2.0 | 12 | 7.0692 | 8.4786 | 19.0 | |
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| 11.2185 | 3.0 | 18 | 6.4881 | 7.8425 | 19.0 | |
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| 9.7688 | 4.0 | 24 | 6.2043 | 7.4958 | 19.0 | |
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| 7.633 | 5.0 | 30 | 6.1694 | 7.4994 | 19.0 | |
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| 10.8618 | 6.0 | 36 | 6.0789 | 7.2123 | 19.0 | |
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| 9.4099 | 7.0 | 42 | 6.0121 | 7.4767 | 19.0 | |
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| 7.1028 | 8.0 | 48 | 5.9718 | 7.4839 | 19.0 | |
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| 10.2013 | 9.0 | 54 | 5.9141 | 8.246 | 19.0 | |
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| 11.8248 | 10.0 | 60 | 5.8562 | 8.4493 | 19.0 | |
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| 6.4776 | 11.0 | 66 | 5.7982 | 8.3904 | 19.0 | |
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| 6.813 | 12.0 | 72 | 5.7229 | 8.6768 | 19.0 | |
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| 10.7703 | 13.0 | 78 | 5.6543 | 8.6985 | 19.0 | |
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| 7.1642 | 14.0 | 84 | 5.6137 | 8.8415 | 19.0 | |
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| 8.1195 | 15.0 | 90 | 5.5589 | 8.9574 | 19.0 | |
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| 10.4234 | 16.0 | 96 | 5.4890 | 8.8876 | 19.0 | |
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| 6.9893 | 17.0 | 102 | 5.4146 | 10.5467 | 19.0 | |
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| 7.3889 | 18.0 | 108 | 5.3484 | 10.5658 | 19.0 | |
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| 6.042 | 19.0 | 114 | 5.3008 | 10.4592 | 19.0 | |
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| 8.1065 | 20.0 | 120 | 5.2775 | 9.958 | 19.0 | |
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| 5.2708 | 21.0 | 126 | 5.2247 | 9.4528 | 19.0 | |
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| 4.9285 | 22.0 | 132 | 5.1740 | 7.2801 | 19.0 | |
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| 4.8751 | 23.0 | 138 | 5.1216 | 7.2902 | 19.0 | |
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| 5.6123 | 24.0 | 144 | 5.0377 | 9.9147 | 19.0 | |
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| 4.6797 | 25.0 | 150 | 4.9345 | 10.7926 | 19.0 | |
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| 4.3882 | 26.0 | 156 | 4.8420 | 10.7388 | 19.0 | |
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| 5.2828 | 27.0 | 162 | 4.7564 | 10.6526 | 19.0 | |
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| 4.2994 | 28.0 | 168 | 4.6960 | 9.7076 | 19.0 | |
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| 3.964 | 29.0 | 174 | 4.5760 | 9.6231 | 19.0 | |
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| 9.4351 | 30.0 | 180 | 4.5173 | 8.9601 | 19.0 | |
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| 5.1911 | 31.0 | 186 | 4.4738 | 9.8122 | 19.0 | |
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| 3.4724 | 32.0 | 192 | 4.4102 | 10.0874 | 19.0 | |
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| 4.39 | 33.0 | 198 | 4.3444 | 10.9115 | 19.0 | |
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| 6.3546 | 34.0 | 204 | 4.2755 | 11.0007 | 18.7619 | |
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| 5.4393 | 35.0 | 210 | 4.2020 | 11.127 | 18.7619 | |
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| 2.8915 | 36.0 | 216 | 4.1248 | 11.0087 | 18.7619 | |
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| 6.6742 | 37.0 | 222 | 4.0757 | 11.4869 | 18.9048 | |
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| 3.5017 | 38.0 | 228 | 4.0376 | 11.4063 | 18.9048 | |
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| 4.1386 | 39.0 | 234 | 3.9890 | 10.7683 | 18.8095 | |
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| 4.9058 | 40.0 | 240 | 3.9372 | 10.7683 | 18.8095 | |
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| 4.2836 | 41.0 | 246 | 3.8872 | 10.8023 | 18.8095 | |
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| 3.7174 | 42.0 | 252 | 3.8378 | 10.9883 | 18.4286 | |
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| 3.0365 | 43.0 | 258 | 3.7907 | 11.0504 | 18.381 | |
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| 3.3476 | 44.0 | 264 | 3.7541 | 11.0634 | 17.9524 | |
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| 3.9578 | 45.0 | 270 | 3.7206 | 11.4798 | 17.4762 | |
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| 4.3193 | 46.0 | 276 | 3.6877 | 11.5753 | 17.3333 | |
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| 3.6244 | 47.0 | 282 | 3.6538 | 11.8793 | 16.5714 | |
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| 2.9136 | 48.0 | 288 | 3.6136 | 12.0169 | 15.9524 | |
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| 2.2932 | 49.0 | 294 | 3.5735 | 11.126 | 16.3333 | |
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| 3.4335 | 50.0 | 300 | 3.5422 | 11.3689 | 16.3333 | |
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| 2.9941 | 51.0 | 306 | 3.5072 | 11.0037 | 16.3333 | |
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| 4.7679 | 52.0 | 312 | 3.4671 | 10.8819 | 16.3333 | |
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| 2.7498 | 53.0 | 318 | 3.4404 | 10.8882 | 16.619 | |
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| 3.5759 | 54.0 | 324 | 3.4195 | 10.8882 | 16.619 | |
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| 2.9012 | 55.0 | 330 | 3.4040 | 10.5862 | 17.3333 | |
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| 3.2823 | 56.0 | 336 | 3.3924 | 10.57 | 17.0476 | |
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| 4.5793 | 57.0 | 342 | 3.3806 | 11.605 | 17.0 | |
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| 4.271 | 58.0 | 348 | 3.3672 | 11.7166 | 16.8095 | |
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| 3.5227 | 59.0 | 354 | 3.3569 | 11.8219 | 16.5238 | |
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| 2.9193 | 60.0 | 360 | 3.3481 | 11.8931 | 16.381 | |
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| 3.5956 | 61.0 | 366 | 3.3385 | 11.1876 | 16.5238 | |
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| 3.5521 | 62.0 | 372 | 3.3293 | 11.0871 | 16.7143 | |
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| 2.6291 | 63.0 | 378 | 3.3136 | 11.2216 | 16.5714 | |
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| 2.0321 | 64.0 | 384 | 3.2935 | 11.29 | 16.381 | |
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| 2.5651 | 65.0 | 390 | 3.2846 | 11.3853 | 16.5714 | |
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| 2.9702 | 66.0 | 396 | 3.2866 | 11.3853 | 16.5714 | |
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| 2.2628 | 67.0 | 402 | 3.2755 | 11.294 | 16.3333 | |
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| 2.5516 | 68.0 | 408 | 3.2619 | 11.699 | 16.1429 | |
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| 3.3097 | 69.0 | 414 | 3.2485 | 11.682 | 16.1429 | |
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| 1.8752 | 70.0 | 420 | 3.2383 | 11.8141 | 15.9048 | |
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| 2.3432 | 71.0 | 426 | 3.2299 | 11.8141 | 15.9048 | |
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| 2.2128 | 72.0 | 432 | 3.2202 | 12.0422 | 15.381 | |
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| 2.7711 | 73.0 | 438 | 3.2107 | 11.9983 | 15.5238 | |
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| 3.7951 | 74.0 | 444 | 3.2039 | 12.2396 | 15.6667 | |
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| 2.7207 | 75.0 | 450 | 3.1969 | 12.9329 | 15.619 | |
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| 2.071 | 76.0 | 456 | 3.1905 | 12.4005 | 15.619 | |
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| 1.9696 | 77.0 | 462 | 3.1861 | 12.5352 | 15.2857 | |
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| 1.2979 | 78.0 | 468 | 3.1816 | 12.5352 | 15.2857 | |
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| 2.6149 | 79.0 | 474 | 3.1777 | 12.5352 | 15.2857 | |
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| 1.7925 | 80.0 | 480 | 3.1720 | 12.5352 | 15.2857 | |
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| 2.3365 | 81.0 | 486 | 3.1683 | 12.4005 | 15.619 | |
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| 3.0536 | 82.0 | 492 | 3.1653 | 12.4005 | 15.619 | |
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| 2.6278 | 83.0 | 498 | 3.1617 | 12.4005 | 15.619 | |
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| 3.2318 | 84.0 | 504 | 3.1583 | 12.4005 | 15.619 | |
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| 2.9789 | 85.0 | 510 | 3.1569 | 12.4005 | 15.619 | |
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| 2.3504 | 86.0 | 516 | 3.1537 | 12.4005 | 15.619 | |
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| 1.603 | 87.0 | 522 | 3.1508 | 12.4005 | 15.619 | |
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| 3.2194 | 88.0 | 528 | 3.1486 | 12.2448 | 16.0952 | |
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| 2.6168 | 89.0 | 534 | 3.1459 | 12.2448 | 16.0952 | |
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| 2.3382 | 90.0 | 540 | 3.1429 | 12.2448 | 16.0952 | |
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| 3.6469 | 91.0 | 546 | 3.1397 | 12.8612 | 15.9048 | |
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| 2.2697 | 92.0 | 552 | 3.1371 | 12.8612 | 15.9048 | |
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| 1.8352 | 93.0 | 558 | 3.1356 | 12.8612 | 15.9048 | |
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| 1.3854 | 94.0 | 564 | 3.1344 | 12.8612 | 15.9048 | |
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| 2.6405 | 95.0 | 570 | 3.1336 | 12.8612 | 15.9048 | |
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| 2.0361 | 96.0 | 576 | 3.1321 | 12.8612 | 15.9048 | |
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| 3.4828 | 97.0 | 582 | 3.1311 | 12.9589 | 15.7619 | |
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| 2.6929 | 98.0 | 588 | 3.1304 | 12.9589 | 15.7619 | |
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| 2.2882 | 99.0 | 594 | 3.1299 | 12.9589 | 15.7619 | |
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| 2.4893 | 100.0 | 600 | 3.1297 | 12.9589 | 15.7619 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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