Merge branch 'master' of ssh://gogs@the-cake-is-a-lie.net:20022/jonas/NLP-LAB.git

Project/sentiment_sentences.csv

@@ -0,0 +1,61 @@
+text;sent
+I am so happy;p
+i love my life;p
+i really like this sunshine;p
+while doing sport i feel free;p
+i is terrible to learn when the weather is this good;n
+i am almost crying when i run out of ice cream;n
+fuck off;n
+you are my best friend ever;p
+i love my mommy;p
+i prefer oral exams;p
+best cocktail is the mojito especial;p
+you got a beautiful wedding;p
+you husband is this handsome;p
+this is such a sneaky bitch;n
+you're kidding;n
+you are really too drunk;n
+you start being annoying;n
+i love my mac;p
+but it would be better if they are less expensive;n
+you are a bad friend;n
+I am in love with my new laptop;p
+You piss me off;n
+I hate school;n
+I'm so mad at you;n
+Seeing you cry, makes me sad;n
+You are so lovely;p
+Fish is disgusting;n
+At times I feel so depressed;n
+Summer makes me happy;p
+I want to dance and sing aloud;p
+Everything will be ok;p
+why are you upset?;n
+I dont like it when it rains;n
+I dont care at all;n
+you are such a bitch;n
+I dont understand what this is all about;n
+give me a break, idiot!;n
+please dont leave me;n
+I love cuddling with my dog;p
+I want to die;n
+that is really sad!;n
+why are you saying that, you moron!;n
+OMG! i love that cat soo much!;p
+can you feel the love tonight;p
+i get so emotional when i watch lion king;p
+i really hate you;n
+that is disgusting;n
+my heart is broken;n
+i love these sunny days;p
+this gave me positive feelings;p
+i am sick;n
+i am tired;n
+are you sick or tired?;n
+you are so cute and sweet;p
+i just lost my mind;n
+i hate all people;n
+you are just dumb;n
+i will get lucky;p
+i like ice cream;p
+go home you idiot;n

Project/simple_approach/Continous_Learner.ipynb

@@ -157,7 +157,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "233f744d595f4b81a362faef6b148fe7",
+       "model_id": "e508c9a1f8634b7ba790cf2f291e215a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -263,7 +263,8 @@
     "           [\n",
     "               [\n",
     "                   (widgets.Text(),\"test_input\"),\n",
-    "                   (widgets.HTML(),\"prediction\")\n",
+    "                   (widgets.HTML(),\"prediction\"),\n",
+    "                   (widgets.Text(value=\"😳😋😀😌😏😔😒😎😢😅😁😉🙌🙏😘😊😩😍😭😂\"),\"prediction_ground_set\")\n",
     "               ],\n",
     "               [\n",
     "                   (widgets.Checkbox(),\"show_sorted_list\"),\n",
@@ -760,9 +761,10 @@
     "            return\n",
     "        X = shown_widgets[\"test_input\"].value\n",
     "        pred = pm.predict([X])\n",
-    "        shown_widgets[\"prediction\"].value = \"<h1> \" + str(stl.sent2emoji(pred)[0]) + \"</h1>\"\n",
+    "        target_list=list(shown_widgets[\"prediction_ground_set\"].value)\n",
+    "        shown_widgets[\"prediction\"].value = \"<h1> \" + str(stl.sent2emoji(pred,custom_target_emojis=target_list)[0]) + \"</h1>\"\n",
     "        if shown_widgets[\"show_sorted_list\"].value:\n",
-    "            mp(\"## \" + \"\".join(stl.edist.sentiment_vector_to_emoji(pred, only_emoticons=True, n_results=100)))\n",
+    "            mp(\"## \" + \"\".join(stl.edist.sentiment_vector_to_emoji(pred, only_emoticons=True, n_results=100, custom_target_emojis=target_list)))\n",
     "        \n",
     "\n",
     "\n",

Project/simple_approach/simple_twitter_learning.py

@@ -68,7 +68,7 @@ def sentiment_score(s):
     #(pos, neg, neu)^T
     return s[0] - s[1]
 
-def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis, style='bo'):
+def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis, style='bo', additional_patches = None):
     # sentiment score axis
     top_X = np.array([sentiment_score(x) for x in top_sentiments])
     pred_X = np.array([sentiment_score(x) for x in predicted_sentiment_vectors])
@@ -86,6 +86,9 @@ def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis
     for i in range(len(top_X)):
         plt.text(top_X[i], top_Y[i], top_emojis[i])
     plt.plot(pred_X, pred_Y, style)
+    for p_tuple in additional_patches:
+        ax_1.add_artist(p_tuple[0])
+        p_tuple[0].set_alpha(0.4)
     plt.savefig("val-error_sentiment-plot" + str(datetime.datetime.now()) +  ".png", bbox_inches='tight')
 
     # sentiment score axis
@@ -105,6 +108,9 @@ def plot_sentiment_space(predicted_sentiment_vectors, top_sentiments, top_emojis
     for i in range(len(top_X)):
         plt.text(top_X[i], top_Y[i], top_emojis[i])
     plt.plot(pred_X, pred_Y, style)
+    for p_tuple in additional_patches:
+        ax_2.add_artist(p_tuple[1])
+        p_tuple[1].set_alpha(0.4)
     plt.savefig("val-error_positive-negative-plot" + str(datetime.datetime.now()) + ".png", bbox_inches='tight')
     plt.show()
 

error_log.csv

@@ -0,0 +1,15 @@
+Train-loss;Train-loss-vector;Valid-loss;Valid-loss-vector;;mean
+0.0148;;0.014416503049941666;[0.01842055, 0.02187643, 0.00295252];5;
+0.0142;;0.013990323407227162;[0.01740025, 0.02176314, 0.00280759];15;
+0.0139;;0.013894867185370585;[0.01726196, 0.02160899, 0.00281365];25;
+0.0134;;0.01334701536721269;[0.01694769 0.02043927 0.00265409];52;[0.5124894,  0.238578,   0.26411116]
+;;;;;
+0.0123;;0.01220267935790051;[0.01521431, 0.01880048, 0.00259325];e2;
+;;;;;
+d2v:;;;;;
+0.0158;;0.015347190550520631;[0.0196343, 0.02333904, 0.00306823];5;
+0.0152;;0.015070546146473468;[0.01918779, 0.02310013, 0.00292371];15;
+0.0150;;0.014911320278768741;[0.01871091, 0.02312384, 0.00289921];25;
+0.0145;;0.014387327237701005;[0.01834857, 0.02200531, 0.0028081 ];52;
+;;;;;
+0.0144;;0.014354445251258958;[0.0182326,  0.0220324,  0.00279834];e2;