Update README.md

README.md

@@ -5,4 +5,31 @@ language:
 base_model:
 - nlptown/bert-base-multilingual-uncased-sentiment
 pipeline_tag: text-classification
----
+---
+
+# Sentiment Analysis Model
+### This model is used in our transcription service, where the audio is first transcribed and then analysed via this model.
+
+The model expects a sentence and return a number from 1 to 5 where 1 is the most negative sentiment and 5 is the most positive one.
+
+The model is trained on BERT (nlptown/bert-base-multilingual-uncased-sentiment), which has an MIT license, and distilled llm results
+
+This model was trained for 20 epochs where the result is:
+
+|              | Precision | Recall | F1-score | Support |
+|--------------|-----------|--------|----------|---------|
+| **Class 1**  | 0.95      | 0.88   | 0.92     | 43      |
+| **Class 2**  | 0.78      | 0.86   | 0.82     | 37      |
+| **Class 3**  | 0.80      | 0.72   | 0.76     | 39      |
+| **Class 4**  | 0.79      | 0.88   | 0.83     | 66      |
+| **Class 5**  | 0.85      | 0.78   | 0.81     | 45      |
+|              |           |        |          |         |
+| **Accuracy** |           |        | 0.83     | 230     |
+| **Macro avg**| 0.84      | 0.82   | 0.83     | 230     |
+| **Weighted avg** | 0.83  | 0.83   | 0.83     | 230     |
+
+## History:
+| Version | Changelog                                                       |
+|---------|-----------------------------------------------------------------|
+| **1.0** | initial training                                                |
+| **1.1** | fine-tuning time and datetime to a neutral sentiment (2 epochs) |