Commit
•
33e604d
1
Parent(s):
499a44f
Upload folder using huggingface_hub
Browse files
README.md
CHANGED
|
@@ -101,57 +101,57 @@ The model was not trained on multi-sentence samples. You should avoid those. Off
|
|
| 101 |
|
| 102 |
### Model Plot
|
| 103 |
|
| 104 |
-
<style>#sk-container-id-
|
| 105 |
-
}#sk-container-id-
|
| 106 |
-
}#sk-container-id-
|
| 107 |
-
}#sk-container-id-
|
| 108 |
-
}#sk-container-id-
|
| 109 |
-
}#sk-container-id-
|
| 110 |
-
}#sk-container-id-
|
| 111 |
}div.sk-parallel-item,
|
| 112 |
div.sk-serial,
|
| 113 |
div.sk-item {/* draw centered vertical line to link estimators */background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));background-size: 2px 100%;background-repeat: no-repeat;background-position: center center;
|
| 114 |
-
}/* Parallel-specific style estimator block */#sk-container-id-
|
| 115 |
-
}#sk-container-id-
|
| 116 |
-
}#sk-container-id-
|
| 117 |
-
}#sk-container-id-
|
| 118 |
-
}#sk-container-id-
|
| 119 |
-
}#sk-container-id-
|
| 120 |
-
}/* Serial-specific style estimator block */#sk-container-id-
|
| 121 |
}/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
|
| 122 |
clickable and can be expanded/collapsed.
|
| 123 |
- Pipeline and ColumnTransformer use this feature and define the default style
|
| 124 |
- Estimators will overwrite some part of the style using the `sk-estimator` class
|
| 125 |
-
*//* Pipeline and ColumnTransformer style (default) */#sk-container-id-
|
| 126 |
}/* Toggleable label */
|
| 127 |
-
#sk-container-id-
|
| 128 |
-
}#sk-container-id-
|
| 129 |
-
}#sk-container-id-
|
| 130 |
-
}/* Toggleable content - dropdown */#sk-container-id-
|
| 131 |
-
}#sk-container-id-
|
| 132 |
-
}#sk-container-id-
|
| 133 |
-
}#sk-container-id-
|
| 134 |
-
}#sk-container-id-
|
| 135 |
-
}#sk-container-id-
|
| 136 |
-
}/* Pipeline/ColumnTransformer-specific style */#sk-container-id-
|
| 137 |
-
}#sk-container-id-
|
| 138 |
}/* Estimator-specific style *//* Colorize estimator box */
|
| 139 |
-
#sk-container-id-
|
| 140 |
-
}#sk-container-id-
|
| 141 |
-
}#sk-container-id-
|
| 142 |
-
#sk-container-id-
|
| 143 |
}/* On hover, darken the color of the background */
|
| 144 |
-
#sk-container-id-
|
| 145 |
}/* Label box, darken color on hover, fitted */
|
| 146 |
-
#sk-container-id-
|
| 147 |
-
}/* Estimator label */#sk-container-id-
|
| 148 |
-
}#sk-container-id-
|
| 149 |
}/* Estimator-specific */
|
| 150 |
-
#sk-container-id-
|
| 151 |
-
}#sk-container-id-
|
| 152 |
}/* on hover */
|
| 153 |
-
#sk-container-id-
|
| 154 |
-
}#sk-container-id-
|
| 155 |
}/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
|
| 156 |
a:link.sk-estimator-doc-link,
|
| 157 |
a:visited.sk-estimator-doc-link {float: right;font-size: smaller;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1em;height: 1em;width: 1em;text-decoration: none !important;margin-left: 1ex;/* unfitted */border: var(--sklearn-color-unfitted-level-1) 1pt solid;color: var(--sklearn-color-unfitted-level-1);
|
|
@@ -171,13 +171,13 @@ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
|
|
| 171 |
.sk-estimator-doc-link span {display: none;z-index: 9999;position: relative;font-weight: normal;right: .2ex;padding: .5ex;margin: .5ex;width: min-content;min-width: 20ex;max-width: 50ex;color: var(--sklearn-color-text);box-shadow: 2pt 2pt 4pt #999;/* unfitted */background: var(--sklearn-color-unfitted-level-0);border: .5pt solid var(--sklearn-color-unfitted-level-3);
|
| 172 |
}.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
|
| 173 |
}.sk-estimator-doc-link:hover span {display: block;
|
| 174 |
-
}/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-
|
| 175 |
-
}#sk-container-id-
|
| 176 |
}/* On hover */
|
| 177 |
-
#sk-container-id-
|
| 178 |
-
}#sk-container-id-
|
| 179 |
}
|
| 180 |
-
</style><div id="sk-container-id-
|
| 181 |
|
| 182 |
## Evaluation Results
|
| 183 |
|
|
@@ -190,6 +190,25 @@ div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
|
|
| 190 |
|
| 191 |
The model is evaluated on validation data from the dataset's test split, using accuracy and F1-score with micro average.
|
| 192 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 193 |
# How to Get Started with the Model
|
| 194 |
|
| 195 |
```python
|
|
@@ -217,22 +236,3 @@ Below you can find information related to citation.
|
|
| 217 |
```
|
| 218 |
[More Information Needed]
|
| 219 |
```
|
| 220 |
-
|
| 221 |
-
# Confusion matrix
|
| 222 |
-
|
| 223 |
-
|
| 224 |
-
|
| 225 |
-
# Classification Report
|
| 226 |
-
|
| 227 |
-
<details>
|
| 228 |
-
<summary> Click to expand </summary>
|
| 229 |
-
|
| 230 |
-
| index | precision | recall | f1-score | support |
|
| 231 |
-
|--------------|-------------|----------|------------|-----------|
|
| 232 |
-
| greeting | 0.977011 | 0.934066 | 0.955056 | 91 |
|
| 233 |
-
| gratitude | 1 | 0.905405 | 0.950355 | 74 |
|
| 234 |
-
| unknown | 0.925466 | 0.993333 | 0.958199 | 150 |
|
| 235 |
-
| macro avg | 0.967492 | 0.944268 | 0.954537 | 315 |
|
| 236 |
-
| weighted avg | 0.957866 | 0.955556 | 0.955448 | 315 |
|
| 237 |
-
|
| 238 |
-
</details>
|
|
|
|
| 101 |
|
| 102 |
### Model Plot
|
| 103 |
|
| 104 |
+
<style>#sk-container-id-17 {/* Definition of color scheme common for light and dark mode */--sklearn-color-text: black;--sklearn-color-line: gray;/* Definition of color scheme for unfitted estimators */--sklearn-color-unfitted-level-0: #fff5e6;--sklearn-color-unfitted-level-1: #f6e4d2;--sklearn-color-unfitted-level-2: #ffe0b3;--sklearn-color-unfitted-level-3: chocolate;/* Definition of color scheme for fitted estimators */--sklearn-color-fitted-level-0: #f0f8ff;--sklearn-color-fitted-level-1: #d4ebff;--sklearn-color-fitted-level-2: #b3dbfd;--sklearn-color-fitted-level-3: cornflowerblue;/* Specific color for light theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));--sklearn-color-icon: #696969;@media (prefers-color-scheme: dark) {/* Redefinition of color scheme for dark theme */--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));--sklearn-color-icon: #878787;}
|
| 105 |
+
}#sk-container-id-17 {color: var(--sklearn-color-text);
|
| 106 |
+
}#sk-container-id-17 pre {padding: 0;
|
| 107 |
+
}#sk-container-id-17 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;
|
| 108 |
+
}#sk-container-id-17 div.sk-dashed-wrapped {border: 1px dashed var(--sklearn-color-line);margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: var(--sklearn-color-background);
|
| 109 |
+
}#sk-container-id-17 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }`but bootstrap.min.css set `[hidden] { display: none !important; }`so we also need the `!important` here to be able to override thedefault hidden behavior on the sphinx rendered scikit-learn.org.See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;
|
| 110 |
+
}#sk-container-id-17 div.sk-text-repr-fallback {display: none;
|
| 111 |
}div.sk-parallel-item,
|
| 112 |
div.sk-serial,
|
| 113 |
div.sk-item {/* draw centered vertical line to link estimators */background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));background-size: 2px 100%;background-repeat: no-repeat;background-position: center center;
|
| 114 |
+
}/* Parallel-specific style estimator block */#sk-container-id-17 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 2px solid var(--sklearn-color-text-on-default-background);flex-grow: 1;
|
| 115 |
+
}#sk-container-id-17 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: var(--sklearn-color-background);position: relative;
|
| 116 |
+
}#sk-container-id-17 div.sk-parallel-item {display: flex;flex-direction: column;
|
| 117 |
+
}#sk-container-id-17 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;
|
| 118 |
+
}#sk-container-id-17 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;
|
| 119 |
+
}#sk-container-id-17 div.sk-parallel-item:only-child::after {width: 0;
|
| 120 |
+
}/* Serial-specific style estimator block */#sk-container-id-17 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: var(--sklearn-color-background);padding-right: 1em;padding-left: 1em;
|
| 121 |
}/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
|
| 122 |
clickable and can be expanded/collapsed.
|
| 123 |
- Pipeline and ColumnTransformer use this feature and define the default style
|
| 124 |
- Estimators will overwrite some part of the style using the `sk-estimator` class
|
| 125 |
+
*//* Pipeline and ColumnTransformer style (default) */#sk-container-id-17 div.sk-toggleable {/* Default theme specific background. It is overwritten whether we have aspecific estimator or a Pipeline/ColumnTransformer */background-color: var(--sklearn-color-background);
|
| 126 |
}/* Toggleable label */
|
| 127 |
+
#sk-container-id-17 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.5em;box-sizing: border-box;text-align: center;
|
| 128 |
+
}#sk-container-id-17 label.sk-toggleable__label-arrow:before {/* Arrow on the left of the label */content: "▸";float: left;margin-right: 0.25em;color: var(--sklearn-color-icon);
|
| 129 |
+
}#sk-container-id-17 label.sk-toggleable__label-arrow:hover:before {color: var(--sklearn-color-text);
|
| 130 |
+
}/* Toggleable content - dropdown */#sk-container-id-17 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
|
| 131 |
+
}#sk-container-id-17 div.sk-toggleable__content.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
|
| 132 |
+
}#sk-container-id-17 div.sk-toggleable__content pre {margin: 0.2em;border-radius: 0.25em;color: var(--sklearn-color-text);/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
|
| 133 |
+
}#sk-container-id-17 div.sk-toggleable__content.fitted pre {/* unfitted */background-color: var(--sklearn-color-fitted-level-0);
|
| 134 |
+
}#sk-container-id-17 input.sk-toggleable__control:checked~div.sk-toggleable__content {/* Expand drop-down */max-height: 200px;max-width: 100%;overflow: auto;
|
| 135 |
+
}#sk-container-id-17 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";
|
| 136 |
+
}/* Pipeline/ColumnTransformer-specific style */#sk-container-id-17 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
|
| 137 |
+
}#sk-container-id-17 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: var(--sklearn-color-fitted-level-2);
|
| 138 |
}/* Estimator-specific style *//* Colorize estimator box */
|
| 139 |
+
#sk-container-id-17 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
|
| 140 |
+
}#sk-container-id-17 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
|
| 141 |
+
}#sk-container-id-17 div.sk-label label.sk-toggleable__label,
|
| 142 |
+
#sk-container-id-17 div.sk-label label {/* The background is the default theme color */color: var(--sklearn-color-text-on-default-background);
|
| 143 |
}/* On hover, darken the color of the background */
|
| 144 |
+
#sk-container-id-17 div.sk-label:hover label.sk-toggleable__label {color: var(--sklearn-color-text);background-color: var(--sklearn-color-unfitted-level-2);
|
| 145 |
}/* Label box, darken color on hover, fitted */
|
| 146 |
+
#sk-container-id-17 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {color: var(--sklearn-color-text);background-color: var(--sklearn-color-fitted-level-2);
|
| 147 |
+
}/* Estimator label */#sk-container-id-17 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;
|
| 148 |
+
}#sk-container-id-17 div.sk-label-container {text-align: center;
|
| 149 |
}/* Estimator-specific */
|
| 150 |
+
#sk-container-id-17 div.sk-estimator {font-family: monospace;border: 1px dotted var(--sklearn-color-border-box);border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;/* unfitted */background-color: var(--sklearn-color-unfitted-level-0);
|
| 151 |
+
}#sk-container-id-17 div.sk-estimator.fitted {/* fitted */background-color: var(--sklearn-color-fitted-level-0);
|
| 152 |
}/* on hover */
|
| 153 |
+
#sk-container-id-17 div.sk-estimator:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-2);
|
| 154 |
+
}#sk-container-id-17 div.sk-estimator.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-2);
|
| 155 |
}/* Specification for estimator info (e.g. "i" and "?") *//* Common style for "i" and "?" */.sk-estimator-doc-link,
|
| 156 |
a:link.sk-estimator-doc-link,
|
| 157 |
a:visited.sk-estimator-doc-link {float: right;font-size: smaller;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1em;height: 1em;width: 1em;text-decoration: none !important;margin-left: 1ex;/* unfitted */border: var(--sklearn-color-unfitted-level-1) 1pt solid;color: var(--sklearn-color-unfitted-level-1);
|
|
|
|
| 171 |
.sk-estimator-doc-link span {display: none;z-index: 9999;position: relative;font-weight: normal;right: .2ex;padding: .5ex;margin: .5ex;width: min-content;min-width: 20ex;max-width: 50ex;color: var(--sklearn-color-text);box-shadow: 2pt 2pt 4pt #999;/* unfitted */background: var(--sklearn-color-unfitted-level-0);border: .5pt solid var(--sklearn-color-unfitted-level-3);
|
| 172 |
}.sk-estimator-doc-link.fitted span {/* fitted */background: var(--sklearn-color-fitted-level-0);border: var(--sklearn-color-fitted-level-3);
|
| 173 |
}.sk-estimator-doc-link:hover span {display: block;
|
| 174 |
+
}/* "?"-specific style due to the `<a>` HTML tag */#sk-container-id-17 a.estimator_doc_link {float: right;font-size: 1rem;line-height: 1em;font-family: monospace;background-color: var(--sklearn-color-background);border-radius: 1rem;height: 1rem;width: 1rem;text-decoration: none;/* unfitted */color: var(--sklearn-color-unfitted-level-1);border: var(--sklearn-color-unfitted-level-1) 1pt solid;
|
| 175 |
+
}#sk-container-id-17 a.estimator_doc_link.fitted {/* fitted */border: var(--sklearn-color-fitted-level-1) 1pt solid;color: var(--sklearn-color-fitted-level-1);
|
| 176 |
}/* On hover */
|
| 177 |
+
#sk-container-id-17 a.estimator_doc_link:hover {/* unfitted */background-color: var(--sklearn-color-unfitted-level-3);color: var(--sklearn-color-background);text-decoration: none;
|
| 178 |
+
}#sk-container-id-17 a.estimator_doc_link.fitted:hover {/* fitted */background-color: var(--sklearn-color-fitted-level-3);
|
| 179 |
}
|
| 180 |
+
</style><div id="sk-container-id-17" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('vect', TfidfVectorizer(ngram_range=(1, 3))),('clf', MultinomialNB(alpha=0.7000000000000001))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-50" type="checkbox" ><label for="sk-estimator-id-50" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted"> Pipeline<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html">?<span>Documentation for Pipeline</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>Pipeline(steps=[('vect', TfidfVectorizer(ngram_range=(1, 3))),('clf', MultinomialNB(alpha=0.7000000000000001))])</pre></div> </div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-51" type="checkbox" ><label for="sk-estimator-id-51" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted"> TfidfVectorizer<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html">?<span>Documentation for TfidfVectorizer</span></a></label><div class="sk-toggleable__content fitted"><pre>TfidfVectorizer(ngram_range=(1, 3))</pre></div> </div></div><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-52" type="checkbox" ><label for="sk-estimator-id-52" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted"> MultinomialNB<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.4/modules/generated/sklearn.naive_bayes.MultinomialNB.html">?<span>Documentation for MultinomialNB</span></a></label><div class="sk-toggleable__content fitted"><pre>MultinomialNB(alpha=0.7000000000000001)</pre></div> </div></div></div></div></div></div>
|
| 181 |
|
| 182 |
## Evaluation Results
|
| 183 |
|
|
|
|
| 190 |
|
| 191 |
The model is evaluated on validation data from the dataset's test split, using accuracy and F1-score with micro average.
|
| 192 |
|
| 193 |
+
#### Confusion matrix
|
| 194 |
+
|
| 195 |
+
|
| 196 |
+
|
| 197 |
+
#### Model description/Evaluation Results/Evaluation Methods/Classification Report
|
| 198 |
+
|
| 199 |
+
<details>
|
| 200 |
+
<summary> Click to expand </summary>
|
| 201 |
+
|
| 202 |
+
| index | precision | recall | f1-score | support |
|
| 203 |
+
|--------------|-------------|----------|------------|-----------|
|
| 204 |
+
| greeting | 0.977011 | 0.934066 | 0.955056 | 91 |
|
| 205 |
+
| gratitude | 1 | 0.905405 | 0.950355 | 74 |
|
| 206 |
+
| unknown | 0.925466 | 0.993333 | 0.958199 | 150 |
|
| 207 |
+
| macro avg | 0.967492 | 0.944268 | 0.954537 | 315 |
|
| 208 |
+
| weighted avg | 0.957866 | 0.955556 | 0.955448 | 315 |
|
| 209 |
+
|
| 210 |
+
</details>
|
| 211 |
+
|
| 212 |
# How to Get Started with the Model
|
| 213 |
|
| 214 |
```python
|
|
|
|
| 236 |
```
|
| 237 |
[More Information Needed]
|
| 238 |
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|