Upload . with huggingface_hub

README.md

@@ -0,0 +1,109 @@
+---
+library_name: sklearn
+tags:
+- sklearn
+- skops
+- text-classification
+---
+
+# Model description
+
+This is a logistic regression model trained with GPT-2 embeddings on imdb dataset.
+
+## Intended uses & limitations
+
+This model is trained for educational purposes.
+
+## Training Procedure
+
+### Hyperparameters
+
+The model is trained with below hyperparameters.
+
+<details>
+<summary> Click to expand </summary>
+
+| Hyperparameter                | Value                                                                                                             |
+|-------------------------------|-------------------------------------------------------------------------------------------------------------------|
+| memory                        |                                                                                                                   |
+| steps                         | [('embedding', HFTransformersLanguage(model_name_or_path='facebook/bart-base')), ('model', LogisticRegression())] |
+| verbose                       | False                                                                                                             |
+| embedding                     | HFTransformersLanguage(model_name_or_path='facebook/bart-base')                                                   |
+| model                         | LogisticRegression()                                                                                              |
+| embedding__model_name_or_path | facebook/bart-base                                                                                                |
+| model__C                      | 1.0                                                                                                               |
+| model__class_weight           |                                                                                                                   |
+| model__dual                   | False                                                                                                             |
+| model__fit_intercept          | True                                                                                                              |
+| model__intercept_scaling      | 1                                                                                                                 |
+| model__l1_ratio               |                                                                                                                   |
+| model__max_iter               | 100                                                                                                               |
+| model__multi_class            | auto                                                                                                              |
+| model__n_jobs                 |                                                                                                                   |
+| model__penalty                | l2                                                                                                                |
+| model__random_state           |                                                                                                                   |
+| model__solver                 | lbfgs                                                                                                             |
+| model__tol                    | 0.0001                                                                                                            |
+| model__verbose                | 0                                                                                                                 |
+| model__warm_start             | False                                                                                                             |
+
+</details>
+
+### Model Plot
+
+The model plot is below.
+
+<style>#sk-c17251a9-68a0-4b34-a80a-a89592893866 {color: black;background-color: white;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 pre{padding: 0;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-toggleable {background-color: white;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 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;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-estimator:hover {background-color: #d4ebff;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-item {z-index: 1;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-parallel-item:only-child::after {width: 0;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;position: relative;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 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 the default 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;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-text-repr-fallback {display: none;}</style><div id="sk-c17251a9-68a0-4b34-a80a-a89592893866" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;embedding&#x27;,HFTransformersLanguage(model_name_or_path=&#x27;facebook/bart-base&#x27;)),(&#x27;model&#x27;, LogisticRegression())])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="cae9454b-9d5c-424d-bbf8-8256c92c6733" type="checkbox" ><label for="cae9454b-9d5c-424d-bbf8-8256c92c6733" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[(&#x27;embedding&#x27;,HFTransformersLanguage(model_name_or_path=&#x27;facebook/bart-base&#x27;)),(&#x27;model&#x27;, LogisticRegression())])</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="0e6ffcb1-dfbc-44ef-9a7c-c15d496369c7" type="checkbox" ><label for="0e6ffcb1-dfbc-44ef-9a7c-c15d496369c7" class="sk-toggleable__label sk-toggleable__label-arrow">HFTransformersLanguage</label><div class="sk-toggleable__content"><pre>HFTransformersLanguage(model_name_or_path=&#x27;facebook/bart-base&#x27;)</pre></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="b8eb1956-cf67-40f5-96f2-c2f0a0a41704" type="checkbox" ><label for="b8eb1956-cf67-40f5-96f2-c2f0a0a41704" class="sk-toggleable__label sk-toggleable__label-arrow">LogisticRegression</label><div class="sk-toggleable__content"><pre>LogisticRegression()</pre></div></div></div></div></div></div></div>
+
+## Evaluation Results
+
+You can find the details about evaluation process and the evaluation results.
+
+
+
+| Metric   |    Value |
+|----------|----------|
+| f1_score | 0.867535 |
+
+# How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+<details>
+<summary> Click to expand </summary>
+
+```python
+[More Information Needed]
+```
+
+</details>
+
+
+
+
+# Model Card Authors
+
+This model card is written by following authors:
+
+[More Information Needed]
+
+# Model Card Contact
+
+You can contact the model card authors through following channels:
+[More Information Needed]
+
+# Citation
+
+Below you can find information related to citation.
+
+**BibTeX:**
+```
+[More Information Needed]
+```
+
+
+# Additional Content
+
+## Confusion matrix
+
+![Confusion matrix](confusion_matrix.png)

config.json

@@ -0,0 +1,18 @@
+{
+    "sklearn": {
+        "environment": [
+            "scikit-learn=1.0.2"
+        ],
+        "example_input": {
+            "data": [
+                "its a totally average film with a few semi-alright action sequences that make the plot seem a little better and remind the viewer of the classic van dam films. parts of the plot don't make sense and seem to be added in to use up time. the end plot is that of a very basic type that doesn't leave the viewer guessing and any twists are obvious from the beginning. the end scene with the flask backs don't make sense as they are added in and seem to have little relevance to the history of van dam's character. not really worth watching again, bit disappointed in the end production, even though it is apparent it was shot on a low budget certain shots and sections in the film are of poor directed quality",
+                "First off let me say, If you haven't enjoyed a Van Damme movie since bloodsport, you probably will not like this movie. Most of these movies may not have the best plots or best actors but I enjoy these kinds of movies for what they are. This movie is much better than any of the movies the other action guys (Segal and Dolph) have thought about putting out the past few years. Van Damme is good in the movie, the movie is only worth watching to Van Damme fans. It is not as good as Wake of Death (which i highly recommend to anyone of likes Van Damme) or In hell but, in my opinion it's worth watching. It has the same type of feel to it as Nowhere to Run. Good fun stuff!",
+                "I had high hopes for this one until they changed the name to 'The Shepherd : Border Patrol, the lamest movie name ever, what was wrong with just 'The Shepherd'. This is a by the numbers action flick that tips its hat at many classic Van Damme films. There is a nice bit of action in a bar which reminded me of hard target and universal soldier but directed with no intensity or flair which is a shame. There is one great line about 'being p*ss drunk and carrying a rabbit' and some OK action scenes let down by the cheapness of it all. A lot of the times the dialogue doesn't match the characters mouth and the stunt men fall down dead a split second before even being shot. The end fight is one of the better Van Damme fights except the Director tries to go a bit too John Woo and fails also introducing flashbacks which no one really cares about just gets in the way of the action which is the whole point of a van Damme film.<br /><br />Not good, not bad, just average generic action."
+            ]
+        },
+        "model": {
+            "file": "pipeline.pkl"
+        },
+        "task": "text-classification"
+    }
+}

pipeline.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:109ba8f7face5a4a938c9c976354633cfe5cb5bf7a6051bf7bdec59e121c43c9
+size 559171012