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final_V1-distilbert-text-classification-model

Text Classification
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distilbert
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AmirlyPhd/final_V1-distilbert-text-classification-model

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  1. README.md +32 -32
  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1232
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- - Accuracy: 0.9743
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- - F1: 0.8372
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- - Precision: 0.8341
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- - Recall: 0.8408
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  ## Model description
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@@ -57,33 +57,33 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 1.7299 | 0.11 | 50 | 1.8504 | 0.2773 | 0.0874 | 0.1995 | 0.1296 |
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- | 0.7996 | 0.22 | 100 | 0.7195 | 0.8242 | 0.5075 | 0.5040 | 0.5175 |
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- | 0.3009 | 0.33 | 150 | 0.4573 | 0.8991 | 0.6736 | 0.6652 | 0.6833 |
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- | 0.2559 | 0.44 | 200 | 0.5667 | 0.8701 | 0.6478 | 0.6293 | 0.6709 |
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- | 0.1636 | 0.55 | 250 | 0.4599 | 0.9040 | 0.6752 | 0.6662 | 0.6864 |
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- | 0.1813 | 0.66 | 300 | 0.3651 | 0.9103 | 0.6823 | 0.8187 | 0.6881 |
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- | 0.1695 | 0.76 | 350 | 0.3603 | 0.9114 | 0.6969 | 0.8090 | 0.7002 |
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- | 0.128 | 0.87 | 400 | 0.3779 | 0.9191 | 0.7197 | 0.7975 | 0.7165 |
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- | 0.0976 | 0.98 | 450 | 0.3244 | 0.9095 | 0.7308 | 0.7394 | 0.7275 |
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- | 0.0867 | 1.09 | 500 | 0.1825 | 0.9617 | 0.8283 | 0.8278 | 0.8294 |
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- | 0.059 | 1.2 | 550 | 0.1847 | 0.9614 | 0.8258 | 0.8234 | 0.8291 |
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- | 0.0719 | 1.31 | 600 | 0.1783 | 0.9590 | 0.8273 | 0.8263 | 0.8287 |
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- | 0.0504 | 1.42 | 650 | 0.1311 | 0.9702 | 0.8325 | 0.8337 | 0.8315 |
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- | 0.0525 | 1.53 | 700 | 0.1531 | 0.9694 | 0.8325 | 0.8355 | 0.8295 |
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- | 0.0193 | 1.64 | 750 | 0.1675 | 0.9666 | 0.8311 | 0.8291 | 0.8334 |
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- | 0.081 | 1.75 | 800 | 0.1531 | 0.9705 | 0.8329 | 0.8306 | 0.8354 |
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- | 0.0453 | 1.86 | 850 | 0.2261 | 0.9295 | 0.7451 | 0.8081 | 0.7321 |
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- | 0.0401 | 1.97 | 900 | 0.2015 | 0.9601 | 0.8283 | 0.8263 | 0.8315 |
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- | 0.0686 | 2.07 | 950 | 0.1674 | 0.9642 | 0.8291 | 0.8255 | 0.8337 |
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- | 0.0353 | 2.18 | 1000 | 0.1639 | 0.9664 | 0.8303 | 0.8264 | 0.8350 |
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- | 0.0345 | 2.29 | 1050 | 0.1830 | 0.9639 | 0.8295 | 0.8264 | 0.8335 |
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- | 0.0212 | 2.4 | 1100 | 0.1978 | 0.9634 | 0.8291 | 0.8258 | 0.8336 |
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- | 0.0028 | 2.51 | 1150 | 0.1864 | 0.9653 | 0.8305 | 0.8273 | 0.8344 |
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- | 0.0023 | 2.62 | 1200 | 0.1906 | 0.9661 | 0.8309 | 0.8277 | 0.8348 |
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- | 0.0076 | 2.73 | 1250 | 0.1826 | 0.9669 | 0.8307 | 0.8278 | 0.8341 |
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- | 0.0272 | 2.84 | 1300 | 0.1830 | 0.9666 | 0.8306 | 0.8283 | 0.8335 |
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- | 0.0065 | 2.95 | 1350 | 0.1908 | 0.9661 | 0.8303 | 0.8278 | 0.8333 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1494
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+ - Accuracy: 0.9672
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+ - F1: 0.8312
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+ - Precision: 0.8275
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+ - Recall: 0.8357
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.6662 | 0.11 | 50 | 1.6945 | 0.2888 | 0.0820 | 0.1958 | 0.1341 |
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+ | 0.7494 | 0.22 | 100 | 0.6947 | 0.8034 | 0.4962 | 0.4949 | 0.5054 |
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+ | 0.2779 | 0.33 | 150 | 0.4631 | 0.8980 | 0.6685 | 0.6550 | 0.6829 |
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+ | 0.2204 | 0.44 | 200 | 0.3938 | 0.8999 | 0.6686 | 0.6659 | 0.6758 |
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+ | 0.137 | 0.55 | 250 | 0.4153 | 0.9065 | 0.6707 | 0.6537 | 0.6898 |
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+ | 0.1931 | 0.66 | 300 | 0.3093 | 0.9166 | 0.7089 | 0.7728 | 0.7046 |
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+ | 0.1356 | 0.76 | 350 | 0.3384 | 0.9152 | 0.6904 | 0.8123 | 0.6978 |
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+ | 0.1065 | 0.87 | 400 | 0.4172 | 0.9144 | 0.7233 | 0.7804 | 0.7174 |
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+ | 0.105 | 0.98 | 450 | 0.4521 | 0.8852 | 0.7078 | 0.7342 | 0.7051 |
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+ | 0.1275 | 1.09 | 500 | 0.2837 | 0.9262 | 0.7365 | 0.7927 | 0.7275 |
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+ | 0.0754 | 1.2 | 550 | 0.3979 | 0.9180 | 0.7164 | 0.8039 | 0.7133 |
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+ | 0.0861 | 1.31 | 600 | 0.1506 | 0.9604 | 0.8259 | 0.8247 | 0.8280 |
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+ | 0.0514 | 1.42 | 650 | 0.1397 | 0.9664 | 0.8277 | 0.8264 | 0.8293 |
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+ | 0.0536 | 1.53 | 700 | 0.1566 | 0.9642 | 0.8279 | 0.8255 | 0.8308 |
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+ | 0.0351 | 1.64 | 750 | 0.1804 | 0.9620 | 0.8276 | 0.8251 | 0.8312 |
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+ | 0.0862 | 1.75 | 800 | 0.1445 | 0.9655 | 0.8314 | 0.8307 | 0.8322 |
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+ | 0.0461 | 1.86 | 850 | 0.1492 | 0.9669 | 0.8306 | 0.8291 | 0.8324 |
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+ | 0.0663 | 1.97 | 900 | 0.2054 | 0.9604 | 0.8292 | 0.8299 | 0.8295 |
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+ | 0.0482 | 2.07 | 950 | 0.1498 | 0.9655 | 0.8294 | 0.8272 | 0.8324 |
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+ | 0.0299 | 2.18 | 1000 | 0.1657 | 0.9650 | 0.8292 | 0.8269 | 0.8321 |
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+ | 0.0348 | 2.29 | 1050 | 0.1473 | 0.9686 | 0.8310 | 0.8291 | 0.8332 |
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+ | 0.0283 | 2.4 | 1100 | 0.1470 | 0.9694 | 0.8333 | 0.8297 | 0.8376 |
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+ | 0.0115 | 2.51 | 1150 | 0.1496 | 0.9691 | 0.8336 | 0.8317 | 0.8358 |
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+ | 0.004 | 2.62 | 1200 | 0.1671 | 0.9650 | 0.8301 | 0.8280 | 0.8329 |
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+ | 0.0054 | 2.73 | 1250 | 0.1560 | 0.9694 | 0.8333 | 0.8325 | 0.8343 |
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+ | 0.0217 | 2.84 | 1300 | 0.1553 | 0.9696 | 0.8334 | 0.8326 | 0.8345 |
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+ | 0.0054 | 2.95 | 1350 | 0.1603 | 0.9691 | 0.8332 | 0.8324 | 0.8343 |
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  ### Framework versions
model.safetensors CHANGED
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