Updated repo and README

README.md

@@ -1,7 +1,6 @@
 ---
-license: mit
 dataset_info:
-  config_name: google_translator
+  config_name: simplified_ekman
   features:
   - name: lt_text
     dtype: string
@@ -65,27 +64,29 @@ dataset_info:
   download_size: 6057071
   dataset_size: 8862855
 configs:
-- config_name: google_translator
+- config_name: simplified_ekman
   data_files:
   - split: train
-    path: google_translator/train-*
+    path: simplified_ekman/train-*
   - split: validation
-    path: google_translator/validation-*
+    path: simplified_ekman/validation-*
   - split: test
-    path: google_translator/test-*
+    path: simplified_ekman/test-*
+license: apache-2.0
 task_categories:
 - text-classification
 language:
-- en
 - lt
+- en
 ---
-Original dataset: [GoEmotions dataset](https://huggingface.co/datasets/google-research-datasets/go_emotions)
 
-The dataset was machine translated to Lithuanian using free Google Translate API.
+# Lithuanian GoEmotions dataset
+
+The original dataset: [GoEmotions](https://huggingface.co/datasets/google-research-datasets/go_emotions) ([paper](https://aclanthology.org/2020.acl-main.372/)).
+
+The derived dataset was machine translated from English into Lithuanian using the free Google Translate API (with [deep-translator](https://pypi.org/project/deep-translator/)). The translation script:
 
-Tool used for translation: [deep-translator](https://pypi.org/project/deep-translator/)
 
-Translation script:
 ```python
 from datasets import load_dataset
 from deep_translator import GoogleTranslator
@@ -102,17 +103,16 @@ def translate_batch(batch):
             translated_batch = translator.translate_batch(original_text)
             break
         except TranslationNotFound:
-            # Translation can fail due to API limits, so we retry until it works
             print(f"Translation failed. Retrying...")
-    
+
     # We fix untranslated entries (None values) by replacing them with the original text
     for i in range(len(translated_batch)):
         if not translated_batch[i]:
             translated_batch[i] = original_text[i]
             print(f"Replaced {original_text[i]} vs {translated_batch[i]}")
-            
-    batch["lt_text"] = translated_batch
-    
+
+    batch["lv_text"] = translated_batch
+
     return batch
 
 translated_dataset = original_dataset.map(
@@ -120,7 +120,9 @@ translated_dataset = original_dataset.map(
 )
 ```
 
-Column `labels` contains multi-label emotion annotations with 28 emotion labels as per GoEmotion dataset:
+The derived dataset uses two aligned tagsets:
+
+- The original 27 + `neutral` emotion labels (may contain more than one label per sample):
 ```yaml
 0: admiration
 1: amusement
@@ -152,7 +154,7 @@ Column `labels` contains multi-label emotion annotations with 28 emotion labels
 27: neutral
 ```
 
-Column `labels_ekman` contains multi-label emotion annotations with 7 base emotions as per Dr. Ekman theory:
+- The basic 6 + `neutral` emotion labels as per [Paul Ekman's theory](https://en.wikipedia.org/wiki/Emotion_classification) (may contain more than one label per sample):
 ```yaml
 0: anger
 1: disgust
@@ -163,8 +165,9 @@ Column `labels_ekman` contains multi-label emotion annotations with 7 base emoti
 6: neutral
 ```
 
-Label mapping from 28 emotions from GoEmotion to 7 base emotions as per Dr. Ekman theory:
-|GoEmotion|Ekman|
+Mapping from the 27 fine-grained emotions to the 6 basic emotions:
+
+|GoEmotions|Ekman|
 |---|---|
 | admiration | joy|
 | amusement | joy|
@@ -193,4 +196,7 @@ Label mapping from 28 emotions from GoEmotion to 7 base emotions as per Dr. Ekma
 | remorse | sadness|
 | sadness | sadness|
 | surprise | surprise|
-| neutral | neutral|
+
+## Acknowledgements
+
+This work was supported by the EU Recovery and Resilience Facility project [Language Technology Initiative](https://www.vti.lu.lv) (2.3.1.1.i.0/1/22/I/CFLA/002).