update readme

README.md

@@ -10,6 +10,15 @@
 
 🔥 Compared with fine-tuning Llama-2 on the same setting, LLaMAX-7B-X-CSQA improves the average accuracy up to 4.2% on the X-CSQA dataset.
 
+
+### Experiments
+
+
+| X-CSQA             | Avg. | Sw   | Ur   | Hi   | Ar    | Vi | Ja | Pl | Zh | Nl | Ru | It | De | Pt    | Fr   | Es | En |
+|--------------------|------|------|------|------|------|----|-------|------|-------|----|------|------|-------|------|-------|--------|--------|
+| Llama2-7B-X-CSQA   | 50.9 | 23.2 | 24.7 | 32.9 | 32.4  | 51.0 | 50.0 | 51.5  | 55.6 | 56.9  | 55.8 | 58.8 | 59.9 | 60.4  | 61.8 | 61.9  | 78.1 | 
+| LLaMAX-7B-X-CSQA   | 55.1 | 43.5 | 39.0 | 44.1 | 45.1  | 54.0 | 49.9 | 54.6 | 58.2 | 58.9 | 57.1 | 59.1 | 59.0 | 60.9  | 61.6 | 62.7 | 74.0 | 
+
 ### Model Usage
 
 Code Example:
@@ -27,13 +36,6 @@ generate_ids = model.generate(inputs.input_ids, max_length=30)
 tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
 # => E
 ```
-### Experiments
-
-
-| X-CSQA             | Avg. | Sw   | Ur   | Hi   | Ar    | Vi | Ja | Pl | Zh | Nl | Ru | It | De | Pt    | Fr   | Es | En |
-|--------------------|------|------|------|------|------|----|-------|------|-------|----|------|------|-------|------|-------|--------|--------|
-| Llama2-7B-X-CSQA   | 50.9 | 23.2 | 24.7 | 32.9 | 32.4  | 51.0 | 50.0 | 51.5  | 55.6 | 56.9  | 55.8 | 58.8 | 59.9 | 60.4  | 61.8 | 61.9  | 78.1 | 
-| LLaMAX-7B-X-CSQA   | 55.1 | 43.5 | 39.0 | 44.1 | 45.1  | 54.0 | 49.9 | 54.6 | 58.2 | 58.9 | 57.1 | 59.1 | 59.0 | 60.9  | 61.6 | 62.7 | 74.0 | 
 
 ### Citation
 if our model helps your work, please cite this paper: