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---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
model-index:
- name: bert-tiny-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-tiny-finetuned-squad
This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1478
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 90
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 29 | 0.8724 |
| No log | 2.0 | 58 | 0.7989 |
| No log | 3.0 | 87 | 0.7316 |
| No log | 4.0 | 116 | 0.6691 |
| No log | 5.0 | 145 | 0.6121 |
| No log | 6.0 | 174 | 0.5597 |
| No log | 7.0 | 203 | 0.5121 |
| No log | 8.0 | 232 | 0.4690 |
| No log | 9.0 | 261 | 0.4300 |
| No log | 10.0 | 290 | 0.3950 |
| No log | 11.0 | 319 | 0.3637 |
| No log | 12.0 | 348 | 0.3358 |
| No log | 13.0 | 377 | 0.3110 |
| No log | 14.0 | 406 | 0.2891 |
| No log | 15.0 | 435 | 0.2697 |
| No log | 16.0 | 464 | 0.2527 |
| No log | 17.0 | 493 | 0.2379 |
| 0.5621 | 18.0 | 522 | 0.2247 |
| 0.5621 | 19.0 | 551 | 0.2134 |
| 0.5621 | 20.0 | 580 | 0.2035 |
| 0.5621 | 21.0 | 609 | 0.1955 |
| 0.5621 | 22.0 | 638 | 0.1886 |
| 0.5621 | 23.0 | 667 | 0.1829 |
| 0.5621 | 24.0 | 696 | 0.1776 |
| 0.5621 | 25.0 | 725 | 0.1731 |
| 0.5621 | 26.0 | 754 | 0.1694 |
| 0.5621 | 27.0 | 783 | 0.1662 |
| 0.5621 | 28.0 | 812 | 0.1635 |
| 0.5621 | 29.0 | 841 | 0.1614 |
| 0.5621 | 30.0 | 870 | 0.1597 |
| 0.5621 | 31.0 | 899 | 0.1582 |
| 0.5621 | 32.0 | 928 | 0.1570 |
| 0.5621 | 33.0 | 957 | 0.1561 |
| 0.5621 | 34.0 | 986 | 0.1551 |
| 0.1726 | 35.0 | 1015 | 0.1545 |
| 0.1726 | 36.0 | 1044 | 0.1537 |
| 0.1726 | 37.0 | 1073 | 0.1532 |
| 0.1726 | 38.0 | 1102 | 0.1528 |
| 0.1726 | 39.0 | 1131 | 0.1523 |
| 0.1726 | 40.0 | 1160 | 0.1519 |
| 0.1726 | 41.0 | 1189 | 0.1516 |
| 0.1726 | 42.0 | 1218 | 0.1512 |
| 0.1726 | 43.0 | 1247 | 0.1510 |
| 0.1726 | 44.0 | 1276 | 0.1507 |
| 0.1726 | 45.0 | 1305 | 0.1505 |
| 0.1726 | 46.0 | 1334 | 0.1503 |
| 0.1726 | 47.0 | 1363 | 0.1502 |
| 0.1726 | 48.0 | 1392 | 0.1500 |
| 0.1726 | 49.0 | 1421 | 0.1499 |
| 0.1726 | 50.0 | 1450 | 0.1497 |
| 0.1726 | 51.0 | 1479 | 0.1496 |
| 0.1271 | 52.0 | 1508 | 0.1496 |
| 0.1271 | 53.0 | 1537 | 0.1494 |
| 0.1271 | 54.0 | 1566 | 0.1493 |
| 0.1271 | 55.0 | 1595 | 0.1492 |
| 0.1271 | 56.0 | 1624 | 0.1491 |
| 0.1271 | 57.0 | 1653 | 0.1490 |
| 0.1271 | 58.0 | 1682 | 0.1490 |
| 0.1271 | 59.0 | 1711 | 0.1489 |
| 0.1271 | 60.0 | 1740 | 0.1489 |
| 0.1271 | 61.0 | 1769 | 0.1488 |
| 0.1271 | 62.0 | 1798 | 0.1487 |
| 0.1271 | 63.0 | 1827 | 0.1487 |
| 0.1271 | 64.0 | 1856 | 0.1486 |
| 0.1271 | 65.0 | 1885 | 0.1486 |
| 0.1271 | 66.0 | 1914 | 0.1485 |
| 0.1271 | 67.0 | 1943 | 0.1485 |
| 0.1271 | 68.0 | 1972 | 0.1484 |
| 0.1216 | 69.0 | 2001 | 0.1484 |
| 0.1216 | 70.0 | 2030 | 0.1483 |
| 0.1216 | 71.0 | 2059 | 0.1483 |
| 0.1216 | 72.0 | 2088 | 0.1482 |
| 0.1216 | 73.0 | 2117 | 0.1483 |
| 0.1216 | 74.0 | 2146 | 0.1482 |
| 0.1216 | 75.0 | 2175 | 0.1481 |
| 0.1216 | 76.0 | 2204 | 0.1481 |
| 0.1216 | 77.0 | 2233 | 0.1481 |
| 0.1216 | 78.0 | 2262 | 0.1480 |
| 0.1216 | 79.0 | 2291 | 0.1480 |
| 0.1216 | 80.0 | 2320 | 0.1479 |
| 0.1216 | 81.0 | 2349 | 0.1479 |
| 0.1216 | 82.0 | 2378 | 0.1479 |
| 0.1216 | 83.0 | 2407 | 0.1479 |
| 0.1216 | 84.0 | 2436 | 0.1479 |
| 0.1216 | 85.0 | 2465 | 0.1479 |
| 0.1216 | 86.0 | 2494 | 0.1478 |
| 0.1151 | 87.0 | 2523 | 0.1478 |
| 0.1151 | 88.0 | 2552 | 0.1478 |
| 0.1151 | 89.0 | 2581 | 0.1478 |
| 0.1151 | 90.0 | 2610 | 0.1478 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1