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---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: sembr2023-distilbert-base-cased
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-distilbert-base-cased
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2214
- Precision: 0.7952
- Recall: 0.8261
- F1: 0.8104
- Iou: 0.6812
- Accuracy: 0.9665
- Balanced Accuracy: 0.9030
- Overall Accuracy: 0.9525
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:--------:|:-----------------:|:----------------:|
| 0.3717 | 0.06 | 10 | 0.3886 | 0 | 0.0 | 0.0 | 0.0 | 0.9133 | 0.5 | 0.9133 |
| 0.3692 | 0.12 | 20 | 0.3552 | 0 | 0.0 | 0.0 | 0.0 | 0.9133 | 0.5 | 0.9133 |
| 0.2579 | 0.17 | 30 | 0.2734 | 0.8923 | 0.1841 | 0.3052 | 0.1801 | 0.9274 | 0.5910 | 0.9255 |
| 0.2135 | 0.23 | 40 | 0.2224 | 0.7632 | 0.6267 | 0.6882 | 0.5247 | 0.9508 | 0.8041 | 0.9348 |
| 0.225 | 0.29 | 50 | 0.1935 | 0.8426 | 0.6378 | 0.7260 | 0.5699 | 0.9583 | 0.8132 | 0.9427 |
| 0.1637 | 0.35 | 60 | 0.1785 | 0.8115 | 0.6951 | 0.7488 | 0.5985 | 0.9596 | 0.8399 | 0.9470 |
| 0.1497 | 0.4 | 70 | 0.1837 | 0.8159 | 0.6961 | 0.7513 | 0.6016 | 0.9601 | 0.8406 | 0.9434 |
| 0.1248 | 0.46 | 80 | 0.1758 | 0.7920 | 0.7523 | 0.7717 | 0.6282 | 0.9614 | 0.8668 | 0.9446 |
| 0.1297 | 0.52 | 90 | 0.1796 | 0.7740 | 0.7933 | 0.7835 | 0.6441 | 0.9620 | 0.8857 | 0.9430 |
| 0.1321 | 0.58 | 100 | 0.1721 | 0.8616 | 0.7178 | 0.7832 | 0.6436 | 0.9656 | 0.8534 | 0.9496 |
| 0.1058 | 0.64 | 110 | 0.1572 | 0.8132 | 0.7766 | 0.7945 | 0.6591 | 0.9652 | 0.8799 | 0.9494 |
| 0.1183 | 0.69 | 120 | 0.1734 | 0.8084 | 0.7792 | 0.7935 | 0.6578 | 0.9649 | 0.8809 | 0.9470 |
| 0.1195 | 0.75 | 130 | 0.1652 | 0.7753 | 0.7952 | 0.7851 | 0.6462 | 0.9623 | 0.8867 | 0.9463 |
| 0.0996 | 0.81 | 140 | 0.1433 | 0.8292 | 0.7684 | 0.7977 | 0.6634 | 0.9662 | 0.8767 | 0.9527 |
| 0.1009 | 0.87 | 150 | 0.1817 | 0.8181 | 0.7808 | 0.7990 | 0.6653 | 0.9660 | 0.8822 | 0.9480 |
| 0.0953 | 0.92 | 160 | 0.1554 | 0.8669 | 0.7245 | 0.7893 | 0.6519 | 0.9665 | 0.8570 | 0.9524 |
| 0.1077 | 0.98 | 170 | 0.1556 | 0.8261 | 0.7752 | 0.7998 | 0.6664 | 0.9664 | 0.8798 | 0.9512 |
| 0.0981 | 1.04 | 180 | 0.1526 | 0.8283 | 0.7703 | 0.7982 | 0.6642 | 0.9663 | 0.8776 | 0.9520 |
| 0.0982 | 1.1 | 190 | 0.1547 | 0.8001 | 0.7976 | 0.7989 | 0.6651 | 0.9652 | 0.8894 | 0.9504 |
| 0.0789 | 1.16 | 200 | 0.1606 | 0.8135 | 0.7947 | 0.8040 | 0.6722 | 0.9664 | 0.8887 | 0.9513 |
| 0.0829 | 1.21 | 210 | 0.1566 | 0.8244 | 0.7872 | 0.8054 | 0.6741 | 0.9670 | 0.8856 | 0.9517 |
| 0.0742 | 1.27 | 220 | 0.1680 | 0.8167 | 0.7895 | 0.8029 | 0.6707 | 0.9664 | 0.8864 | 0.9506 |
| 0.084 | 1.33 | 230 | 0.1680 | 0.8197 | 0.7824 | 0.8006 | 0.6675 | 0.9662 | 0.8830 | 0.9511 |
| 0.0702 | 1.39 | 240 | 0.1653 | 0.8184 | 0.7996 | 0.8089 | 0.6791 | 0.9673 | 0.8914 | 0.9510 |
| 0.0713 | 1.45 | 250 | 0.1675 | 0.7844 | 0.8184 | 0.8010 | 0.6681 | 0.9648 | 0.8985 | 0.9492 |
| 0.0763 | 1.5 | 260 | 0.1501 | 0.8239 | 0.7833 | 0.8031 | 0.6710 | 0.9667 | 0.8837 | 0.9532 |
| 0.0738 | 1.56 | 270 | 0.1518 | 0.8203 | 0.7962 | 0.8081 | 0.6780 | 0.9672 | 0.8898 | 0.9527 |
| 0.0736 | 1.62 | 280 | 0.1624 | 0.7849 | 0.8222 | 0.8031 | 0.6710 | 0.9651 | 0.9004 | 0.9508 |
| 0.0659 | 1.68 | 290 | 0.1735 | 0.7775 | 0.8308 | 0.8033 | 0.6712 | 0.9647 | 0.9041 | 0.9496 |
| 0.0653 | 1.73 | 300 | 0.1586 | 0.7828 | 0.8224 | 0.8022 | 0.6697 | 0.9648 | 0.9004 | 0.9503 |
| 0.0635 | 1.79 | 310 | 0.1720 | 0.8091 | 0.8033 | 0.8062 | 0.6753 | 0.9665 | 0.8927 | 0.9510 |
| 0.0724 | 1.85 | 320 | 0.1588 | 0.8057 | 0.8033 | 0.8045 | 0.6729 | 0.9662 | 0.8925 | 0.9531 |
| 0.0612 | 1.91 | 330 | 0.1818 | 0.7828 | 0.8222 | 0.8020 | 0.6695 | 0.9648 | 0.9003 | 0.9488 |
| 0.0612 | 1.97 | 340 | 0.1704 | 0.8235 | 0.7893 | 0.8060 | 0.6751 | 0.9671 | 0.8866 | 0.9526 |
| 0.0592 | 2.02 | 350 | 0.1634 | 0.8002 | 0.7929 | 0.7965 | 0.6618 | 0.9649 | 0.8870 | 0.9520 |
| 0.0474 | 2.08 | 360 | 0.1835 | 0.7931 | 0.8120 | 0.8025 | 0.6701 | 0.9654 | 0.8960 | 0.9506 |
| 0.0484 | 2.14 | 370 | 0.1790 | 0.8123 | 0.7941 | 0.8031 | 0.6710 | 0.9663 | 0.8883 | 0.9522 |
| 0.0524 | 2.2 | 380 | 0.1812 | 0.7702 | 0.8291 | 0.7985 | 0.6646 | 0.9637 | 0.9028 | 0.9499 |
| 0.052 | 2.25 | 390 | 0.1716 | 0.8041 | 0.7964 | 0.8002 | 0.6670 | 0.9655 | 0.8890 | 0.9533 |
| 0.0443 | 2.31 | 400 | 0.1676 | 0.8054 | 0.7976 | 0.8015 | 0.6687 | 0.9658 | 0.8897 | 0.9535 |
| 0.057 | 2.37 | 410 | 0.1836 | 0.8028 | 0.8084 | 0.8056 | 0.6745 | 0.9662 | 0.8948 | 0.9507 |
| 0.0414 | 2.43 | 420 | 0.1791 | 0.8049 | 0.8053 | 0.8051 | 0.6737 | 0.9662 | 0.8934 | 0.9527 |
| 0.0471 | 2.49 | 430 | 0.1771 | 0.7964 | 0.8126 | 0.8044 | 0.6728 | 0.9658 | 0.8965 | 0.9527 |
| 0.039 | 2.54 | 440 | 0.1773 | 0.8066 | 0.8021 | 0.8043 | 0.6727 | 0.9662 | 0.8919 | 0.9537 |
| 0.0543 | 2.6 | 450 | 0.1855 | 0.7887 | 0.8193 | 0.8037 | 0.6718 | 0.9653 | 0.8992 | 0.9511 |
| 0.0398 | 2.66 | 460 | 0.1959 | 0.7938 | 0.8147 | 0.8041 | 0.6724 | 0.9656 | 0.8973 | 0.9504 |
| 0.0419 | 2.72 | 470 | 0.1944 | 0.7847 | 0.8286 | 0.8060 | 0.6751 | 0.9654 | 0.9035 | 0.9498 |
| 0.0436 | 2.77 | 480 | 0.1869 | 0.8002 | 0.8109 | 0.8055 | 0.6744 | 0.9661 | 0.8958 | 0.9520 |
| 0.0497 | 2.83 | 490 | 0.1850 | 0.7736 | 0.8422 | 0.8065 | 0.6757 | 0.9650 | 0.9094 | 0.9501 |
| 0.0408 | 2.89 | 500 | 0.1883 | 0.8178 | 0.7962 | 0.8068 | 0.6762 | 0.9670 | 0.8897 | 0.9527 |
| 0.0332 | 2.95 | 510 | 0.1883 | 0.7913 | 0.8188 | 0.8048 | 0.6733 | 0.9656 | 0.8991 | 0.9516 |
| 0.0382 | 3.01 | 520 | 0.2008 | 0.7914 | 0.8307 | 0.8106 | 0.6815 | 0.9664 | 0.9049 | 0.9515 |
| 0.047 | 3.06 | 530 | 0.1913 | 0.8137 | 0.8013 | 0.8075 | 0.6771 | 0.9669 | 0.8920 | 0.9522 |
| 0.0327 | 3.12 | 540 | 0.1969 | 0.7993 | 0.8168 | 0.8080 | 0.6778 | 0.9664 | 0.8987 | 0.9518 |
| 0.0338 | 3.18 | 550 | 0.1989 | 0.7962 | 0.8173 | 0.8066 | 0.6759 | 0.9660 | 0.8987 | 0.9518 |
| 0.0332 | 3.24 | 560 | 0.2004 | 0.7999 | 0.8178 | 0.8087 | 0.6789 | 0.9665 | 0.8992 | 0.9518 |
| 0.0308 | 3.29 | 570 | 0.1964 | 0.8126 | 0.8092 | 0.8109 | 0.6819 | 0.9673 | 0.8957 | 0.9537 |
| 0.0348 | 3.35 | 580 | 0.2032 | 0.7902 | 0.8239 | 0.8067 | 0.6761 | 0.9658 | 0.9016 | 0.9515 |
| 0.0351 | 3.41 | 590 | 0.2064 | 0.7855 | 0.8218 | 0.8032 | 0.6712 | 0.9651 | 0.9003 | 0.9511 |
| 0.0301 | 3.47 | 600 | 0.2118 | 0.7872 | 0.8265 | 0.8063 | 0.6755 | 0.9656 | 0.9026 | 0.9505 |
| 0.0261 | 3.53 | 610 | 0.1997 | 0.7991 | 0.8194 | 0.8091 | 0.6794 | 0.9665 | 0.8999 | 0.9522 |
| 0.0282 | 3.58 | 620 | 0.1950 | 0.8029 | 0.8114 | 0.8071 | 0.6766 | 0.9664 | 0.8962 | 0.9527 |
| 0.0326 | 3.64 | 630 | 0.2038 | 0.7873 | 0.8290 | 0.8076 | 0.6773 | 0.9658 | 0.9039 | 0.9516 |
| 0.0353 | 3.7 | 640 | 0.2010 | 0.7930 | 0.8228 | 0.8076 | 0.6773 | 0.9660 | 0.9012 | 0.9514 |
| 0.0348 | 3.76 | 650 | 0.2043 | 0.7949 | 0.8243 | 0.8093 | 0.6797 | 0.9663 | 0.9021 | 0.9519 |
| 0.0296 | 3.82 | 660 | 0.2050 | 0.7976 | 0.8226 | 0.8099 | 0.6805 | 0.9665 | 0.9014 | 0.9529 |
| 0.0287 | 3.87 | 670 | 0.2158 | 0.7820 | 0.8318 | 0.8061 | 0.6752 | 0.9653 | 0.9049 | 0.9504 |
| 0.024 | 3.93 | 680 | 0.2110 | 0.7847 | 0.8294 | 0.8065 | 0.6757 | 0.9655 | 0.9039 | 0.9512 |
| 0.0274 | 3.99 | 690 | 0.2075 | 0.7937 | 0.8254 | 0.8092 | 0.6796 | 0.9663 | 0.9025 | 0.9523 |
| 0.0247 | 4.05 | 700 | 0.2130 | 0.7995 | 0.8210 | 0.8101 | 0.6808 | 0.9666 | 0.9007 | 0.9525 |
| 0.0202 | 4.1 | 710 | 0.2142 | 0.7955 | 0.8215 | 0.8083 | 0.6782 | 0.9662 | 0.9007 | 0.9518 |
| 0.0245 | 4.16 | 720 | 0.2120 | 0.7965 | 0.8195 | 0.8078 | 0.6776 | 0.9662 | 0.8998 | 0.9516 |
| 0.0214 | 4.22 | 730 | 0.2151 | 0.7899 | 0.8256 | 0.8074 | 0.6770 | 0.9659 | 0.9024 | 0.9515 |
| 0.0202 | 4.28 | 740 | 0.2145 | 0.7963 | 0.8220 | 0.8089 | 0.6792 | 0.9664 | 0.9010 | 0.9520 |
| 0.0257 | 4.34 | 750 | 0.2181 | 0.7960 | 0.8217 | 0.8087 | 0.6788 | 0.9663 | 0.9009 | 0.9520 |
| 0.0271 | 4.39 | 760 | 0.2151 | 0.7953 | 0.8232 | 0.8090 | 0.6793 | 0.9663 | 0.9015 | 0.9518 |
| 0.0279 | 4.45 | 770 | 0.2196 | 0.7955 | 0.8237 | 0.8094 | 0.6798 | 0.9664 | 0.9018 | 0.9521 |
| 0.0273 | 4.51 | 780 | 0.2194 | 0.7984 | 0.8256 | 0.8118 | 0.6832 | 0.9668 | 0.9029 | 0.9523 |
| 0.018 | 4.57 | 790 | 0.2201 | 0.7985 | 0.8247 | 0.8114 | 0.6826 | 0.9668 | 0.9025 | 0.9526 |
| 0.0275 | 4.62 | 800 | 0.2204 | 0.7893 | 0.8358 | 0.8119 | 0.6834 | 0.9664 | 0.9073 | 0.9519 |
| 0.0198 | 4.68 | 810 | 0.2160 | 0.7983 | 0.8232 | 0.8105 | 0.6814 | 0.9666 | 0.9017 | 0.9526 |
| 0.019 | 4.74 | 820 | 0.2109 | 0.7961 | 0.8243 | 0.8100 | 0.6806 | 0.9665 | 0.9021 | 0.9527 |
| 0.0236 | 4.8 | 830 | 0.2208 | 0.7956 | 0.8238 | 0.8094 | 0.6799 | 0.9664 | 0.9019 | 0.9521 |
| 0.0177 | 4.86 | 840 | 0.2217 | 0.7900 | 0.8301 | 0.8095 | 0.6800 | 0.9661 | 0.9046 | 0.9519 |
| 0.0209 | 4.91 | 850 | 0.2226 | 0.7927 | 0.8285 | 0.8102 | 0.6810 | 0.9664 | 0.9040 | 0.9522 |
| 0.0241 | 4.97 | 860 | 0.2215 | 0.7915 | 0.8276 | 0.8091 | 0.6794 | 0.9662 | 0.9035 | 0.9521 |
| 0.0211 | 5.03 | 870 | 0.2181 | 0.7957 | 0.8242 | 0.8097 | 0.6802 | 0.9664 | 0.9020 | 0.9525 |
| 0.0234 | 5.09 | 880 | 0.2171 | 0.7975 | 0.8224 | 0.8098 | 0.6803 | 0.9665 | 0.9013 | 0.9526 |
| 0.0201 | 5.14 | 890 | 0.2191 | 0.7925 | 0.8265 | 0.8092 | 0.6795 | 0.9662 | 0.9030 | 0.9523 |
| 0.0211 | 5.2 | 900 | 0.2175 | 0.7957 | 0.8238 | 0.8095 | 0.6799 | 0.9664 | 0.9019 | 0.9526 |
| 0.0234 | 5.26 | 910 | 0.2207 | 0.7913 | 0.8291 | 0.8097 | 0.6803 | 0.9662 | 0.9042 | 0.9522 |
| 0.023 | 5.32 | 920 | 0.2202 | 0.7965 | 0.8234 | 0.8098 | 0.6803 | 0.9665 | 0.9017 | 0.9524 |
| 0.0192 | 5.38 | 930 | 0.2203 | 0.7969 | 0.8239 | 0.8102 | 0.6809 | 0.9665 | 0.9020 | 0.9525 |
| 0.0217 | 5.43 | 940 | 0.2206 | 0.7956 | 0.8255 | 0.8103 | 0.6811 | 0.9665 | 0.9027 | 0.9524 |
| 0.0195 | 5.49 | 950 | 0.2213 | 0.7953 | 0.8259 | 0.8103 | 0.6811 | 0.9665 | 0.9029 | 0.9524 |
| 0.0285 | 5.55 | 960 | 0.2214 | 0.7955 | 0.8254 | 0.8102 | 0.6809 | 0.9665 | 0.9026 | 0.9524 |
| 0.0263 | 5.61 | 970 | 0.2213 | 0.7955 | 0.8254 | 0.8102 | 0.6809 | 0.9665 | 0.9026 | 0.9524 |
| 0.02 | 5.66 | 980 | 0.2214 | 0.7951 | 0.8258 | 0.8101 | 0.6809 | 0.9665 | 0.9028 | 0.9524 |
| 0.021 | 5.72 | 990 | 0.2214 | 0.7952 | 0.8261 | 0.8104 | 0.6812 | 0.9665 | 0.9030 | 0.9525 |
| 0.0233 | 5.78 | 1000 | 0.2214 | 0.7952 | 0.8261 | 0.8104 | 0.6812 | 0.9665 | 0.9030 | 0.9525 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1
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