Update README.md

README.md

@@ -17,6 +17,9 @@ metrics:
 Argument Mining model trained with English (EN) data for the Argument Relation Identification (ARI) task using the US2016 and the QT30 corpora. 
 This a fine-tuned [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) model, inspired by "Transformer-Based Models for Automatic Detection of Argument Relations: A Cross-Domain Evaluation" paper.
 
+<br>
+
+This model was trained on the full dataset: train and test merged.
 
 ## Usage
 ```python
@@ -42,6 +45,22 @@ model_inputs = tokenizer(text_one, text_two, return_tensors="pt")
 model_output = model(**model_inputs)
 ```
 
+## Metrics
+
+```
+              precision    recall  f1-score   support
+
+           0       0.51      0.59      0.55       833
+           1       0.46      0.28      0.35       200
+           2       0.51      0.30      0.38       156
+           3       0.82      0.82      0.82      2209
+
+    accuracy                           0.71      3398
+   macro avg       0.58      0.50      0.53      3398
+weighted avg       0.71      0.71      0.71      3398
+```
+Theses results for the model that was trained only on train chunk of data and tested on the test one.
+
 Cite:
 
 ```