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--- |
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license: mit |
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base_model: prajjwal1/bert-tiny |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-tiny-finetuned-squad |
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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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# bert-tiny-finetuned-squad |
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1478 |
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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: 90 |
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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 | 29 | 0.8724 | |
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| No log | 2.0 | 58 | 0.7989 | |
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| No log | 3.0 | 87 | 0.7316 | |
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| No log | 4.0 | 116 | 0.6691 | |
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| No log | 5.0 | 145 | 0.6121 | |
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| No log | 6.0 | 174 | 0.5597 | |
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| No log | 7.0 | 203 | 0.5121 | |
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| No log | 8.0 | 232 | 0.4690 | |
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| No log | 9.0 | 261 | 0.4300 | |
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| No log | 10.0 | 290 | 0.3950 | |
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| No log | 11.0 | 319 | 0.3637 | |
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| No log | 12.0 | 348 | 0.3358 | |
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| No log | 13.0 | 377 | 0.3110 | |
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| No log | 14.0 | 406 | 0.2891 | |
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| No log | 15.0 | 435 | 0.2697 | |
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| No log | 16.0 | 464 | 0.2527 | |
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| No log | 17.0 | 493 | 0.2379 | |
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| 0.5621 | 18.0 | 522 | 0.2247 | |
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| 0.5621 | 19.0 | 551 | 0.2134 | |
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| 0.5621 | 20.0 | 580 | 0.2035 | |
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| 0.5621 | 21.0 | 609 | 0.1955 | |
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| 0.5621 | 22.0 | 638 | 0.1886 | |
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| 0.5621 | 23.0 | 667 | 0.1829 | |
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| 0.5621 | 24.0 | 696 | 0.1776 | |
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| 0.5621 | 25.0 | 725 | 0.1731 | |
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| 0.5621 | 26.0 | 754 | 0.1694 | |
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| 0.5621 | 27.0 | 783 | 0.1662 | |
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| 0.5621 | 28.0 | 812 | 0.1635 | |
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| 0.5621 | 29.0 | 841 | 0.1614 | |
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| 0.5621 | 30.0 | 870 | 0.1597 | |
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| 0.5621 | 31.0 | 899 | 0.1582 | |
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| 0.5621 | 32.0 | 928 | 0.1570 | |
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| 0.5621 | 33.0 | 957 | 0.1561 | |
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| 0.5621 | 34.0 | 986 | 0.1551 | |
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| 0.1726 | 35.0 | 1015 | 0.1545 | |
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| 0.1726 | 36.0 | 1044 | 0.1537 | |
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| 0.1726 | 37.0 | 1073 | 0.1532 | |
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| 0.1726 | 38.0 | 1102 | 0.1528 | |
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| 0.1726 | 39.0 | 1131 | 0.1523 | |
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| 0.1726 | 40.0 | 1160 | 0.1519 | |
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| 0.1726 | 41.0 | 1189 | 0.1516 | |
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| 0.1726 | 42.0 | 1218 | 0.1512 | |
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| 0.1726 | 43.0 | 1247 | 0.1510 | |
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| 0.1726 | 44.0 | 1276 | 0.1507 | |
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| 0.1726 | 45.0 | 1305 | 0.1505 | |
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| 0.1726 | 46.0 | 1334 | 0.1503 | |
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| 0.1726 | 47.0 | 1363 | 0.1502 | |
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| 0.1726 | 48.0 | 1392 | 0.1500 | |
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| 0.1726 | 49.0 | 1421 | 0.1499 | |
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| 0.1726 | 50.0 | 1450 | 0.1497 | |
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| 0.1726 | 51.0 | 1479 | 0.1496 | |
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| 0.1271 | 52.0 | 1508 | 0.1496 | |
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| 0.1271 | 53.0 | 1537 | 0.1494 | |
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| 0.1271 | 54.0 | 1566 | 0.1493 | |
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| 0.1271 | 55.0 | 1595 | 0.1492 | |
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| 0.1271 | 56.0 | 1624 | 0.1491 | |
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| 0.1271 | 57.0 | 1653 | 0.1490 | |
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| 0.1271 | 58.0 | 1682 | 0.1490 | |
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| 0.1271 | 59.0 | 1711 | 0.1489 | |
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| 0.1271 | 60.0 | 1740 | 0.1489 | |
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| 0.1271 | 61.0 | 1769 | 0.1488 | |
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| 0.1271 | 62.0 | 1798 | 0.1487 | |
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| 0.1271 | 63.0 | 1827 | 0.1487 | |
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| 0.1271 | 64.0 | 1856 | 0.1486 | |
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| 0.1271 | 65.0 | 1885 | 0.1486 | |
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| 0.1271 | 66.0 | 1914 | 0.1485 | |
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| 0.1271 | 67.0 | 1943 | 0.1485 | |
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| 0.1271 | 68.0 | 1972 | 0.1484 | |
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| 0.1216 | 69.0 | 2001 | 0.1484 | |
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| 0.1216 | 70.0 | 2030 | 0.1483 | |
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| 0.1216 | 71.0 | 2059 | 0.1483 | |
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| 0.1216 | 72.0 | 2088 | 0.1482 | |
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| 0.1216 | 73.0 | 2117 | 0.1483 | |
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| 0.1216 | 74.0 | 2146 | 0.1482 | |
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| 0.1216 | 75.0 | 2175 | 0.1481 | |
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| 0.1216 | 76.0 | 2204 | 0.1481 | |
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| 0.1216 | 77.0 | 2233 | 0.1481 | |
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| 0.1216 | 78.0 | 2262 | 0.1480 | |
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| 0.1216 | 79.0 | 2291 | 0.1480 | |
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| 0.1216 | 80.0 | 2320 | 0.1479 | |
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| 0.1216 | 81.0 | 2349 | 0.1479 | |
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| 0.1216 | 82.0 | 2378 | 0.1479 | |
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| 0.1216 | 83.0 | 2407 | 0.1479 | |
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| 0.1216 | 84.0 | 2436 | 0.1479 | |
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| 0.1216 | 85.0 | 2465 | 0.1479 | |
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| 0.1216 | 86.0 | 2494 | 0.1478 | |
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| 0.1151 | 87.0 | 2523 | 0.1478 | |
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| 0.1151 | 88.0 | 2552 | 0.1478 | |
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| 0.1151 | 89.0 | 2581 | 0.1478 | |
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| 0.1151 | 90.0 | 2610 | 0.1478 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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