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---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: sembr2023-bert-tiny
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. -->
# sembr2023-bert-tiny
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: 0.2101
- Precision: 0.7983
- Recall: 0.6561
- F1: 0.7202
- Iou: 0.5628
- Accuracy: 0.9531
- Balanced Accuracy: 0.8196
- Overall Accuracy: 0.9387
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Iou | Accuracy | Balanced Accuracy | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:--------:|:-----------------:|:----------------:|
| 1.2554 | 0.06 | 10 | 1.1550 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.8047 | 0.12 | 20 | 0.7616 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.6392 | 0.18 | 30 | 0.6116 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.5328 | 0.24 | 40 | 0.5384 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.4859 | 0.3 | 50 | 0.4982 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.469 | 0.36 | 60 | 0.4726 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.4711 | 0.42 | 70 | 0.4513 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.4341 | 0.48 | 80 | 0.4349 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.4234 | 0.55 | 90 | 0.4181 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.3661 | 0.61 | 100 | 0.3970 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.3901 | 0.67 | 110 | 0.3685 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
| 0.3493 | 0.73 | 120 | 0.3447 | 0.6074 | 0.0126 | 0.0247 | 0.0125 | 0.9084 | 0.5059 | 0.9081 |
| 0.3199 | 0.79 | 130 | 0.3309 | 0.6329 | 0.0676 | 0.1222 | 0.0651 | 0.9106 | 0.5318 | 0.9095 |
| 0.3444 | 0.85 | 140 | 0.3219 | 0.6748 | 0.1406 | 0.2328 | 0.1317 | 0.9147 | 0.5669 | 0.9130 |
| 0.3131 | 0.91 | 150 | 0.3158 | 0.6768 | 0.2211 | 0.3334 | 0.2000 | 0.9187 | 0.6052 | 0.9154 |
| 0.2921 | 0.97 | 160 | 0.3100 | 0.7245 | 0.1708 | 0.2765 | 0.1604 | 0.9178 | 0.5821 | 0.9156 |
| 0.3121 | 1.03 | 170 | 0.3057 | 0.6425 | 0.3246 | 0.4313 | 0.2749 | 0.9213 | 0.6531 | 0.9157 |
| 0.3267 | 1.09 | 180 | 0.3035 | 0.6597 | 0.3155 | 0.4269 | 0.2714 | 0.9221 | 0.6495 | 0.9168 |
| 0.28 | 1.15 | 190 | 0.2986 | 0.6836 | 0.3429 | 0.4567 | 0.2960 | 0.9250 | 0.6634 | 0.9171 |
| 0.2945 | 1.21 | 200 | 0.2929 | 0.7005 | 0.3078 | 0.4276 | 0.2720 | 0.9242 | 0.6472 | 0.9177 |
| 0.2744 | 1.27 | 210 | 0.2874 | 0.7108 | 0.3406 | 0.4606 | 0.2992 | 0.9266 | 0.6633 | 0.9183 |
| 0.2563 | 1.33 | 220 | 0.2866 | 0.6712 | 0.4432 | 0.5339 | 0.3641 | 0.9288 | 0.7106 | 0.9182 |
| 0.2565 | 1.39 | 230 | 0.2793 | 0.7057 | 0.4187 | 0.5256 | 0.3565 | 0.9305 | 0.7005 | 0.9203 |
| 0.2383 | 1.45 | 240 | 0.2760 | 0.6918 | 0.4493 | 0.5448 | 0.3744 | 0.9309 | 0.7145 | 0.9197 |
| 0.2477 | 1.52 | 250 | 0.2698 | 0.7317 | 0.4190 | 0.5328 | 0.3632 | 0.9324 | 0.7017 | 0.9218 |
| 0.2466 | 1.58 | 260 | 0.2674 | 0.7119 | 0.4605 | 0.5593 | 0.3882 | 0.9332 | 0.7208 | 0.9212 |
| 0.2623 | 1.64 | 270 | 0.2641 | 0.7071 | 0.4675 | 0.5629 | 0.3917 | 0.9332 | 0.7240 | 0.9220 |
| 0.2308 | 1.7 | 280 | 0.2622 | 0.7169 | 0.4797 | 0.5748 | 0.4033 | 0.9347 | 0.7303 | 0.9225 |
| 0.2179 | 1.76 | 290 | 0.2577 | 0.7287 | 0.4678 | 0.5698 | 0.3984 | 0.9350 | 0.7251 | 0.9236 |
| 0.2347 | 1.82 | 300 | 0.2557 | 0.7425 | 0.4651 | 0.5719 | 0.4005 | 0.9360 | 0.7244 | 0.9246 |
| 0.2175 | 1.88 | 310 | 0.2549 | 0.7314 | 0.4873 | 0.5849 | 0.4133 | 0.9364 | 0.7346 | 0.9244 |
| 0.2365 | 1.94 | 320 | 0.2524 | 0.7237 | 0.5057 | 0.5954 | 0.4239 | 0.9368 | 0.7431 | 0.9244 |
| 0.2068 | 2.0 | 330 | 0.2513 | 0.7569 | 0.4744 | 0.5832 | 0.4117 | 0.9376 | 0.7295 | 0.9260 |
| 0.2004 | 2.06 | 340 | 0.2506 | 0.6962 | 0.5462 | 0.6122 | 0.4411 | 0.9363 | 0.7611 | 0.9234 |
| 0.231 | 2.12 | 350 | 0.2490 | 0.7145 | 0.5251 | 0.6053 | 0.4340 | 0.9370 | 0.7519 | 0.9241 |
| 0.2117 | 2.18 | 360 | 0.2457 | 0.7300 | 0.5132 | 0.6027 | 0.4314 | 0.9378 | 0.7470 | 0.9257 |
| 0.1768 | 2.24 | 370 | 0.2450 | 0.7281 | 0.5273 | 0.6116 | 0.4405 | 0.9384 | 0.7537 | 0.9256 |
| 0.2013 | 2.3 | 380 | 0.2433 | 0.7198 | 0.5513 | 0.6244 | 0.4539 | 0.9390 | 0.7648 | 0.9258 |
| 0.2128 | 2.36 | 390 | 0.2405 | 0.7568 | 0.5214 | 0.6174 | 0.4466 | 0.9406 | 0.7522 | 0.9282 |
| 0.2186 | 2.42 | 400 | 0.2393 | 0.7560 | 0.5215 | 0.6173 | 0.4464 | 0.9405 | 0.7522 | 0.9279 |
| 0.2105 | 2.48 | 410 | 0.2408 | 0.6966 | 0.5834 | 0.6350 | 0.4652 | 0.9383 | 0.7788 | 0.9246 |
| 0.2216 | 2.55 | 420 | 0.2382 | 0.7415 | 0.5493 | 0.6311 | 0.4610 | 0.9409 | 0.7650 | 0.9277 |
| 0.1816 | 2.61 | 430 | 0.2377 | 0.7258 | 0.5768 | 0.6428 | 0.4736 | 0.9410 | 0.7774 | 0.9274 |
| 0.2136 | 2.67 | 440 | 0.2352 | 0.7506 | 0.5456 | 0.6319 | 0.4619 | 0.9415 | 0.7636 | 0.9284 |
| 0.2043 | 2.73 | 450 | 0.2341 | 0.7425 | 0.5615 | 0.6394 | 0.4700 | 0.9418 | 0.7709 | 0.9286 |
| 0.2014 | 2.79 | 460 | 0.2333 | 0.7565 | 0.5572 | 0.6417 | 0.4725 | 0.9428 | 0.7695 | 0.9297 |
| 0.1862 | 2.85 | 470 | 0.2306 | 0.7744 | 0.5520 | 0.6446 | 0.4755 | 0.9440 | 0.7678 | 0.9313 |
| 0.1714 | 2.91 | 480 | 0.2312 | 0.7354 | 0.6083 | 0.6658 | 0.4991 | 0.9438 | 0.7931 | 0.9302 |
| 0.1693 | 2.97 | 490 | 0.2280 | 0.7637 | 0.5768 | 0.6572 | 0.4895 | 0.9447 | 0.7794 | 0.9314 |
| 0.2043 | 3.03 | 500 | 0.2288 | 0.7577 | 0.5848 | 0.6601 | 0.4927 | 0.9446 | 0.7830 | 0.9314 |
| 0.2138 | 3.09 | 510 | 0.2256 | 0.7797 | 0.5650 | 0.6552 | 0.4872 | 0.9453 | 0.7744 | 0.9327 |
| 0.1914 | 3.15 | 520 | 0.2250 | 0.7732 | 0.5873 | 0.6675 | 0.5010 | 0.9462 | 0.7849 | 0.9330 |
| 0.1647 | 3.21 | 530 | 0.2240 | 0.7586 | 0.6173 | 0.6807 | 0.5160 | 0.9467 | 0.7987 | 0.9329 |
| 0.1749 | 3.27 | 540 | 0.2237 | 0.7679 | 0.6108 | 0.6804 | 0.5156 | 0.9472 | 0.7961 | 0.9331 |
| 0.1883 | 3.33 | 550 | 0.2226 | 0.7839 | 0.5992 | 0.6792 | 0.5143 | 0.9479 | 0.7913 | 0.9344 |
| 0.1657 | 3.39 | 560 | 0.2196 | 0.7856 | 0.6059 | 0.6841 | 0.5199 | 0.9485 | 0.7946 | 0.9353 |
| 0.1721 | 3.45 | 570 | 0.2217 | 0.7556 | 0.6408 | 0.6935 | 0.5308 | 0.9479 | 0.8099 | 0.9335 |
| 0.1843 | 3.52 | 580 | 0.2188 | 0.7935 | 0.6010 | 0.6840 | 0.5197 | 0.9489 | 0.7926 | 0.9354 |
| 0.1709 | 3.58 | 590 | 0.2175 | 0.7993 | 0.6078 | 0.6905 | 0.5273 | 0.9499 | 0.7962 | 0.9364 |
| 0.1526 | 3.64 | 600 | 0.2168 | 0.7782 | 0.6380 | 0.7012 | 0.5398 | 0.9500 | 0.8098 | 0.9358 |
| 0.1614 | 3.7 | 610 | 0.2148 | 0.8129 | 0.6083 | 0.6959 | 0.5336 | 0.9511 | 0.7971 | 0.9380 |
| 0.1585 | 3.76 | 620 | 0.2149 | 0.8046 | 0.6210 | 0.7010 | 0.5396 | 0.9513 | 0.8029 | 0.9377 |
| 0.1798 | 3.82 | 630 | 0.2163 | 0.7788 | 0.6476 | 0.7072 | 0.5470 | 0.9507 | 0.8145 | 0.9364 |
| 0.1637 | 3.88 | 640 | 0.2147 | 0.8000 | 0.6276 | 0.7034 | 0.5425 | 0.9513 | 0.8059 | 0.9375 |
| 0.1542 | 3.94 | 650 | 0.2138 | 0.8004 | 0.6335 | 0.7072 | 0.5471 | 0.9518 | 0.8088 | 0.9379 |
| 0.1575 | 4.0 | 660 | 0.2146 | 0.7867 | 0.6464 | 0.7097 | 0.5500 | 0.9514 | 0.8143 | 0.9371 |
| 0.1632 | 4.06 | 670 | 0.2124 | 0.7998 | 0.6368 | 0.7091 | 0.5493 | 0.9519 | 0.8103 | 0.9380 |
| 0.1687 | 4.12 | 680 | 0.2112 | 0.8129 | 0.6294 | 0.7095 | 0.5498 | 0.9526 | 0.8074 | 0.9390 |
| 0.1565 | 4.18 | 690 | 0.2129 | 0.7959 | 0.6429 | 0.7113 | 0.5519 | 0.9520 | 0.8131 | 0.9380 |
| 0.1869 | 4.24 | 700 | 0.2128 | 0.7896 | 0.6526 | 0.7146 | 0.5559 | 0.9521 | 0.8175 | 0.9378 |
| 0.1689 | 4.3 | 710 | 0.2119 | 0.8052 | 0.6361 | 0.7107 | 0.5512 | 0.9524 | 0.8102 | 0.9385 |
| 0.1581 | 4.36 | 720 | 0.2126 | 0.7817 | 0.6618 | 0.7167 | 0.5585 | 0.9519 | 0.8215 | 0.9373 |
| 0.1683 | 4.42 | 730 | 0.2121 | 0.8019 | 0.6442 | 0.7145 | 0.5558 | 0.9526 | 0.8140 | 0.9384 |
| 0.1735 | 4.48 | 740 | 0.2111 | 0.8009 | 0.6452 | 0.7147 | 0.5560 | 0.9526 | 0.8145 | 0.9387 |
| 0.1537 | 4.55 | 750 | 0.2104 | 0.7991 | 0.6461 | 0.7145 | 0.5558 | 0.9525 | 0.8148 | 0.9386 |
| 0.174 | 4.61 | 760 | 0.2112 | 0.8031 | 0.6454 | 0.7156 | 0.5572 | 0.9528 | 0.8147 | 0.9387 |
| 0.1662 | 4.67 | 770 | 0.2118 | 0.7897 | 0.6586 | 0.7182 | 0.5603 | 0.9525 | 0.8204 | 0.9378 |
| 0.1486 | 4.73 | 780 | 0.2113 | 0.8009 | 0.6492 | 0.7171 | 0.5590 | 0.9529 | 0.8164 | 0.9386 |
| 0.1672 | 4.79 | 790 | 0.2110 | 0.8055 | 0.6461 | 0.7170 | 0.5589 | 0.9531 | 0.8152 | 0.9389 |
| 0.1553 | 4.85 | 800 | 0.2108 | 0.7969 | 0.6527 | 0.7176 | 0.5596 | 0.9528 | 0.8179 | 0.9383 |
| 0.1504 | 4.91 | 810 | 0.2106 | 0.8047 | 0.6461 | 0.7167 | 0.5585 | 0.9530 | 0.8151 | 0.9389 |
| 0.176 | 4.97 | 820 | 0.2103 | 0.8059 | 0.6459 | 0.7171 | 0.5589 | 0.9531 | 0.8151 | 0.9389 |
| 0.1597 | 5.03 | 830 | 0.2102 | 0.7979 | 0.6535 | 0.7185 | 0.5607 | 0.9529 | 0.8184 | 0.9386 |
| 0.1437 | 5.09 | 840 | 0.2105 | 0.7977 | 0.6539 | 0.7187 | 0.5609 | 0.9529 | 0.8185 | 0.9385 |
| 0.1751 | 5.15 | 850 | 0.2104 | 0.8004 | 0.6508 | 0.7179 | 0.5600 | 0.9530 | 0.8172 | 0.9386 |
| 0.1737 | 5.21 | 860 | 0.2105 | 0.7951 | 0.6573 | 0.7197 | 0.5621 | 0.9529 | 0.8201 | 0.9385 |
| 0.1683 | 5.27 | 870 | 0.2104 | 0.7953 | 0.6573 | 0.7198 | 0.5622 | 0.9529 | 0.8201 | 0.9385 |
| 0.1477 | 5.33 | 880 | 0.2102 | 0.7974 | 0.6536 | 0.7184 | 0.5605 | 0.9529 | 0.8184 | 0.9386 |
| 0.1702 | 5.39 | 890 | 0.2102 | 0.7978 | 0.6532 | 0.7183 | 0.5604 | 0.9529 | 0.8182 | 0.9386 |
| 0.1478 | 5.45 | 900 | 0.2101 | 0.7985 | 0.6536 | 0.7188 | 0.5611 | 0.9530 | 0.8185 | 0.9386 |
| 0.1656 | 5.52 | 910 | 0.2099 | 0.8 | 0.6522 | 0.7186 | 0.5608 | 0.9530 | 0.8179 | 0.9387 |
| 0.1757 | 5.58 | 920 | 0.2099 | 0.7996 | 0.6525 | 0.7186 | 0.5608 | 0.9530 | 0.8180 | 0.9387 |
| 0.1723 | 5.64 | 930 | 0.2100 | 0.7990 | 0.6536 | 0.7190 | 0.5613 | 0.9530 | 0.8185 | 0.9387 |
| 0.1472 | 5.7 | 940 | 0.2101 | 0.7976 | 0.6561 | 0.7199 | 0.5624 | 0.9531 | 0.8196 | 0.9386 |
| 0.1628 | 5.76 | 950 | 0.2102 | 0.7974 | 0.6564 | 0.7201 | 0.5626 | 0.9531 | 0.8198 | 0.9386 |
| 0.1563 | 5.82 | 960 | 0.2102 | 0.7973 | 0.6564 | 0.7200 | 0.5626 | 0.9531 | 0.8198 | 0.9386 |
| 0.1893 | 5.88 | 970 | 0.2102 | 0.7979 | 0.6563 | 0.7202 | 0.5628 | 0.9531 | 0.8197 | 0.9387 |
| 0.1554 | 5.94 | 980 | 0.2101 | 0.7982 | 0.6562 | 0.7203 | 0.5628 | 0.9531 | 0.8197 | 0.9387 |
| 0.1636 | 6.0 | 990 | 0.2101 | 0.7983 | 0.6561 | 0.7202 | 0.5628 | 0.9531 | 0.8196 | 0.9387 |
| 0.1588 | 6.06 | 1000 | 0.2101 | 0.7983 | 0.6561 | 0.7202 | 0.5628 | 0.9531 | 0.8196 | 0.9387 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1
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