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multilingual_go_emotions_V1.1

Text Classification
Safetensors
bert
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@@ -40,36 +40,74 @@ This repository/space contains details about a multilingual emotion classificati
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  The following table shows the performance metrics of the fine-tuned model on the test set, broken down by emotion category.
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- | index | accuracy | precision | recall | f1 | mcc | support | threshold |
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- |----------------|----------|-----------|--------|-------|-------|---------|-----------|
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- | admiration | 0.942 | 0.652 | 0.684 | 0.667 | 0.636 | 2790 | 0.4 |
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- | amusement | 0.973 | 0.735 | 0.817 | 0.774 | 0.76 | 1866 | 0.35 |
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- | anger | 0.96 | 0.411 | 0.364 | 0.386 | 0.366 | 1128 | 0.35 |
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- | annoyance | 0.896 | 0.246 | 0.481 | 0.325 | 0.293 | 1704 | 0.15 |
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- | approval | 0.91 | 0.329 | 0.383 | 0.354 | 0.307 | 2094 | 0.2 |
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- | caring | 0.958 | 0.285 | 0.46 | 0.352 | 0.341 | 816 | 0.15 |
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- | confusion | 0.965 | 0.444 | 0.401 | 0.421 | 0.404 | 1020 | 0.25 |
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- | curiosity | 0.935 | 0.433 | 0.74 | 0.546 | 0.535 | 1734 | 0.25 |
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- | desire | 0.984 | 0.404 | 0.534 | 0.46 | 0.457 | 414 | 0.25 |
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- | disappointment | 0.942 | 0.224 | 0.345 | 0.272 | 0.249 | 1014 | 0.15 |
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- | disapproval | 0.935 | 0.306 | 0.413 | 0.352 | 0.322 | 1398 | 0.25 |
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- | disgust | 0.975 | 0.343 | 0.418 | 0.377 | 0.366 | 600 | 0.15 |
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- | embarrassment | 0.99 | 0.28 | 0.242 | 0.26 | 0.255 | 240 | 0.1 |
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- | excitement | 0.973 | 0.344 | 0.425 | 0.38 | 0.369 | 624 | 0.15 |
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- | fear | 0.987 | 0.599 | 0.522 | 0.558 | 0.553 | 498 | 0.35 |
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- | gratitude | 0.989 | 0.924 | 0.902 | 0.913 | 0.907 | 2004 | 0.4 |
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- | grief | 0.999 | 0 | 0 | 0 | 0 | 36 | 0.05 |
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- | joy | 0.965 | 0.454 | 0.532 | 0.49 | 0.474 | 1032 | 0.25 |
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- | love | 0.973 | 0.731 | 0.829 | 0.777 | 0.765 | 1812 | 0.35 |
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- | nervousness | 0.996 | 0.385 | 0.25 | 0.303 | 0.308 | 120 | 0.1 |
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- | optimism | 0.973 | 0.588 | 0.525 | 0.555 | 0.542 | 1062 | 0.25 |
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- | pride | 0.997 | 0 | 0 | 0 | 0 | 84 | 0.05 |
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- | realization | 0.962 | 0.202 | 0.189 | 0.195 | 0.176 | 792 | 0.15 |
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- | relief | 0.996 | 0 | 0 | 0 | 0 | 138 | 0.05 |
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- | remorse | 0.988 | 0.597 | 0.808 | 0.687 | 0.689 | 516 | 0.15 |
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- | sadness | 0.97 | 0.548 | 0.434 | 0.484 | 0.473 | 1062 | 0.4 |
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- | surprise | 0.974 | 0.487 | 0.569 | 0.524 | 0.513 | 828 | 0.3 |
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- | neutral | 0.726 | 0.551 | 0.818 | 0.658 | 0.468 | 10524 | 0.2 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Fine-tuning Performance
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  The following table shows the performance metrics of the fine-tuned model on the test set, broken down by emotion category.
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+ The table below shows the performance of the test model:
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+
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+ | Labels | Accuracy | Precision | Recall | F1 | MCC | Support | Threshold |
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+ | -------------- | -------- | --------- | ------ | ------ | ------- | ------- | --------- |
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+ | admiration | 0.935 | 0.616 | 0.629 | 0.622 | 0.587 | 2790 | 0.20 |
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+ | amusement | 0.969 | 0.706 | 0.800 | 0.750 | 0.735 | 1866 | 0.10 |
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+ | anger | 0.956 | 0.360 | 0.344 | 0.352 | 0.329 | 1128 | 0.10 |
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+ | annoyance | 0.925 | 0.274 | 0.263 | 0.268 | 0.229 | 1704 | 0.10 |
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+ | approval | 0.904 | 0.286 | 0.330 | 0.306 | 0.256 | 2094 | 0.10 |
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+ | caring | 0.962 | 0.299 | 0.370 | 0.331 | 0.314 | 816 | 0.10 |
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+ | confusion | 0.961 | 0.369 | 0.333 | 0.350 | 0.331 | 1020 | 0.35 |
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+ | curiosity | 0.932 | 0.404 | 0.569 | 0.473 | 0.445 | 1734 | 0.10 |
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+ | desire | 0.985 | 0.412 | 0.418 | 0.415 | 0.407 | 414 | 0.35 |
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+ | disappointment | 0.959 | 0.276 | 0.204 | 0.235 | 0.217 | 1014 | 0.25 |
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+ | disapproval | 0.926 | 0.238 | 0.324 | 0.275 | 0.240 | 1398 | 0.10 |
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+ | disgust | 0.977 | 0.364 | 0.297 | 0.327 | 0.317 | 600 | 0.25 |
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+ | embarrassment | 0.993 | 0.538 | 0.292 | 0.378 | 0.393 | 240 | 0.85 |
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+ | excitement | 0.971 | 0.285 | 0.327 | 0.305 | 0.291 | 624 | 0.20 |
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+ | fear | 0.986 | 0.562 | 0.474 | 0.514 | 0.509 | 498 | 0.40 |
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+ | gratitude | 0.989 | 0.928 | 0.890 | 0.909 | 0.903 | 2004 | 0.75 |
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+ | grief | 0.998 | 0.273 | 0.333 | 0.300 | 0.301 | 36 | 0.15 |
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+ | joy | 0.959 | 0.382 | 0.453 | 0.415 | 0.396 | 1032 | 0.20 |
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+ | love | 0.972 | 0.734 | 0.780 | 0.757 | 0.742 | 1812 | 0.20 |
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+ | nervousness | 0.995 | 0.339 | 0.358 | 0.348 | 0.346 | 120 | 0.20 |
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+ | optimism | 0.970 | 0.553 | 0.427 | 0.482 | 0.471 | 1062 | 0.45 |
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+ | pride | 0.997 | 0.387 | 0.286 | 0.329 | 0.331 | 84 | 0.15 |
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+ | realization | 0.964 | 0.191 | 0.152 | 0.169 | 0.152 | 792 | 0.25 |
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+ | relief | 0.992 | 0.129 | 0.145 | 0.137 | 0.133 | 138 | 0.10 |
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+ | remorse | 0.986 | 0.566 | 0.614 | 0.589 | 0.583 | 516 | 0.25 |
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+ | sadness | 0.968 | 0.506 | 0.444 | 0.473 | 0.457 | 1062 | 0.40 |
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+ | surprise | 0.973 | 0.465 | 0.450 | 0.457 | 0.444 | 828 | 0.45 |
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+ | neutral | 0.731 | 0.577 | 0.630 | 0.602 | 0.400 | 10524 | 0.10 |
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+
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+ ### Test Model Performance (Threshold = 0.5)
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+
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+ The table below shows the performance of the test model with a threshold of 0.5:
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+
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+ | Label | Accuracy | Precision | Recall | F1 | MCC | Support | Threshold |
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+ | -------------- | -------- | --------- | ------ | ------ | ------- | ------- | --------- |
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+ | admiration | 0.939 | 0.678 | 0.542 | 0.603 | 0.574 | 2790 | 0.5 |
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+ | amusement | 0.970 | 0.760 | 0.693 | 0.725 | 0.710 | 1866 | 0.5 |
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+ | anger | 0.964 | 0.471 | 0.210 | 0.291 | 0.299 | 1128 | 0.5 |
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+ | annoyance | 0.944 | 0.383 | 0.100 | 0.158 | 0.175 | 1704 | 0.5 |
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+ | approval | 0.934 | 0.472 | 0.176 | 0.256 | 0.260 | 2094 | 0.5 |
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+ | caring | 0.973 | 0.424 | 0.246 | 0.312 | 0.310 | 816 | 0.5 |
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+ | confusion | 0.964 | 0.399 | 0.310 | 0.349 | 0.333 | 1020 | 0.5 |
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+ | curiosity | 0.945 | 0.480 | 0.375 | 0.421 | 0.396 | 1734 | 0.5 |
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+ | desire | 0.985 | 0.420 | 0.394 | 0.406 | 0.399 | 414 | 0.5 |
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+ | disappointment | 0.964 | 0.333 | 0.169 | 0.224 | 0.220 | 1014 | 0.5 |
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+ | disapproval | 0.950 | 0.338 | 0.163 | 0.220 | 0.212 | 1398 | 0.5 |
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+ | disgust | 0.979 | 0.390 | 0.252 | 0.306 | 0.303 | 600 | 0.5 |
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+ | embarrassment | 0.992 | 0.430 | 0.333 | 0.376 | 0.375 | 240 | 0.5 |
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+ | excitement | 0.976 | 0.324 | 0.237 | 0.274 | 0.265 | 624 | 0.5 |
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+ | fear | 0.987 | 0.576 | 0.458 | 0.510 | 0.507 | 498 | 0.5 |
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+ | gratitude | 0.988 | 0.905 | 0.903 | 0.904 | 0.898 | 2004 | 0.5 |
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+ | grief | 0.999 | 0.294 | 0.139 | 0.189 | 0.202 | 36 | 0.5 |
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+ | joy | 0.964 | 0.422 | 0.355 | 0.385 | 0.369 | 1032 | 0.5 |
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+ | love | 0.972 | 0.771 | 0.714 | 0.741 | 0.727 | 1812 | 0.5 |
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+ | nervousness | 0.995 | 0.351 | 0.275 | 0.308 | 0.308 | 120 | 0.5 |
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+ | optimism | 0.971 | 0.566 | 0.416 | 0.480 | 0.471 | 1062 | 0.5 |
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+ | pride | 0.997 | 0.432 | 0.226 | 0.297 | 0.311 | 84 | 0.5 |
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+ | realization | 0.969 | 0.231 | 0.117 | 0.156 | 0.150 | 792 | 0.5 |
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+ | relief | 0.994 | 0.143 | 0.065 | 0.090 | 0.094 | 138 | 0.5 |
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+ | remorse | 0.987 | 0.603 | 0.562 | 0.582 | 0.576 | 516 | 0.5 |
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+ | sadness | 0.969 | 0.531 | 0.424 | 0.471 | 0.458 | 1062 | 0.5 |
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+ | surprise | 0.973 | 0.465 | 0.436 | 0.450 | 0.436 | 828 | 0.5 |
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+ | neutral | 0.742 | 0.670 | 0.400 | 0.501 | 0.362 | 10524 | 0.5 |
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+
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  ## Fine-tuning Performance
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