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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: alpaca-test |
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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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# alpaca-test |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4690 |
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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: 4 |
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- eval_batch_size: 4 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 13 | 10.1816 | |
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| No log | 2.0 | 26 | 6.3483 | |
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| No log | 3.0 | 39 | 3.6923 | |
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| No log | 4.0 | 52 | 1.9466 | |
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| No log | 5.0 | 65 | 1.0837 | |
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| No log | 6.0 | 78 | 0.8578 | |
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| No log | 7.0 | 91 | 0.8170 | |
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| No log | 8.0 | 104 | 0.7665 | |
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| No log | 9.0 | 117 | 0.7464 | |
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| No log | 10.0 | 130 | 0.7227 | |
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| No log | 11.0 | 143 | 0.7066 | |
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| No log | 12.0 | 156 | 0.6916 | |
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| No log | 13.0 | 169 | 0.6775 | |
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| No log | 14.0 | 182 | 0.6691 | |
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| No log | 15.0 | 195 | 0.6563 | |
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| No log | 16.0 | 208 | 0.6450 | |
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| No log | 17.0 | 221 | 0.6352 | |
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| No log | 18.0 | 234 | 0.6260 | |
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| No log | 19.0 | 247 | 0.6178 | |
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| No log | 20.0 | 260 | 0.6083 | |
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| No log | 21.0 | 273 | 0.6015 | |
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| No log | 22.0 | 286 | 0.5942 | |
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| No log | 23.0 | 299 | 0.5873 | |
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| No log | 24.0 | 312 | 0.5821 | |
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| No log | 25.0 | 325 | 0.5774 | |
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| No log | 26.0 | 338 | 0.5718 | |
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| No log | 27.0 | 351 | 0.5663 | |
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| No log | 28.0 | 364 | 0.5618 | |
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| No log | 29.0 | 377 | 0.5573 | |
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| No log | 30.0 | 390 | 0.5529 | |
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| No log | 31.0 | 403 | 0.5492 | |
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| No log | 32.0 | 416 | 0.5455 | |
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| No log | 33.0 | 429 | 0.5427 | |
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| No log | 34.0 | 442 | 0.5394 | |
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| No log | 35.0 | 455 | 0.5366 | |
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| No log | 36.0 | 468 | 0.5336 | |
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| No log | 37.0 | 481 | 0.5310 | |
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| No log | 38.0 | 494 | 0.5288 | |
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| No log | 39.0 | 507 | 0.5265 | |
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| No log | 40.0 | 520 | 0.5237 | |
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| No log | 41.0 | 533 | 0.5211 | |
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| No log | 42.0 | 546 | 0.5190 | |
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| No log | 43.0 | 559 | 0.5165 | |
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| No log | 44.0 | 572 | 0.5143 | |
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| No log | 45.0 | 585 | 0.5130 | |
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| No log | 46.0 | 598 | 0.5115 | |
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| No log | 47.0 | 611 | 0.5101 | |
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| No log | 48.0 | 624 | 0.5085 | |
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| No log | 49.0 | 637 | 0.5067 | |
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| No log | 50.0 | 650 | 0.5051 | |
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| No log | 51.0 | 663 | 0.5035 | |
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| No log | 52.0 | 676 | 0.5021 | |
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| No log | 53.0 | 689 | 0.5008 | |
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| No log | 54.0 | 702 | 0.4992 | |
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| No log | 55.0 | 715 | 0.4979 | |
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| No log | 56.0 | 728 | 0.4963 | |
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| No log | 57.0 | 741 | 0.4950 | |
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| No log | 58.0 | 754 | 0.4937 | |
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| No log | 59.0 | 767 | 0.4924 | |
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| No log | 60.0 | 780 | 0.4911 | |
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| No log | 61.0 | 793 | 0.4899 | |
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| No log | 62.0 | 806 | 0.4886 | |
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| No log | 63.0 | 819 | 0.4874 | |
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| No log | 64.0 | 832 | 0.4869 | |
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| No log | 65.0 | 845 | 0.4861 | |
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| No log | 66.0 | 858 | 0.4850 | |
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| No log | 67.0 | 871 | 0.4838 | |
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| No log | 68.0 | 884 | 0.4828 | |
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| No log | 69.0 | 897 | 0.4817 | |
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| No log | 70.0 | 910 | 0.4808 | |
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| No log | 71.0 | 923 | 0.4799 | |
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| No log | 72.0 | 936 | 0.4790 | |
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| No log | 73.0 | 949 | 0.4781 | |
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| No log | 74.0 | 962 | 0.4776 | |
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| No log | 75.0 | 975 | 0.4769 | |
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| No log | 76.0 | 988 | 0.4763 | |
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| 1.1637 | 77.0 | 1001 | 0.4756 | |
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| 1.1637 | 78.0 | 1014 | 0.4751 | |
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| 1.1637 | 79.0 | 1027 | 0.4744 | |
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| 1.1637 | 80.0 | 1040 | 0.4739 | |
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| 1.1637 | 81.0 | 1053 | 0.4734 | |
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| 1.1637 | 82.0 | 1066 | 0.4729 | |
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| 1.1637 | 83.0 | 1079 | 0.4725 | |
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| 1.1637 | 84.0 | 1092 | 0.4722 | |
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| 1.1637 | 85.0 | 1105 | 0.4719 | |
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| 1.1637 | 86.0 | 1118 | 0.4716 | |
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| 1.1637 | 87.0 | 1131 | 0.4713 | |
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| 1.1637 | 88.0 | 1144 | 0.4710 | |
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| 1.1637 | 89.0 | 1157 | 0.4707 | |
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| 1.1637 | 90.0 | 1170 | 0.4703 | |
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| 1.1637 | 91.0 | 1183 | 0.4701 | |
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| 1.1637 | 92.0 | 1196 | 0.4699 | |
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| 1.1637 | 93.0 | 1209 | 0.4697 | |
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| 1.1637 | 94.0 | 1222 | 0.4695 | |
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| 1.1637 | 95.0 | 1235 | 0.4694 | |
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| 1.1637 | 96.0 | 1248 | 0.4692 | |
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| 1.1637 | 97.0 | 1261 | 0.4691 | |
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| 1.1637 | 98.0 | 1274 | 0.4691 | |
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| 1.1637 | 99.0 | 1287 | 0.4691 | |
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| 1.1637 | 100.0 | 1300 | 0.4690 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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