Update README.md

README.md

@@ -132,10 +132,7 @@ As shown in the table, our SeaLLM model outperforms most 13B baselines and reach
 | Llama-2-13b-chat      | 61.17 | 43.29 | 39.97 | 35.50 | 23.74
 | Polylm-13b-chat       | 32.23 | 29.26 | 29.01 | 25.36 | 18.08
 | Qwen-PolyLM-7b-chat   | 53.65 | 61.58 | 39.26 | 33.69 | 29.02
-| SeaLLM-13b/78k-step   | 58.19 | 41.95 | 46.56 | 37.63 | 31.00
-| SeaLLM-13bChat/SFT/v1 | 63.53 | 45.47 | 50.25 | 39.85 | 36.07
-| SeaLLM-13bChat/SFT/v2 | 62.35 | 45.81 | 49.92 | 40.04 | 36.49
-
+| SeaLLM-13b-chat       | 63.53 | 46.31 | 49.25 | 40.61 | 36.30
 
 
 ### MMLU - Preserving English-based knowledge
@@ -164,8 +161,7 @@ As shown in the table below, the 1-shot reading comprehension performance is sig
 |-----------| ------- | ------- |  ------- | ------- | ------- | ------- | ------- | 
 | Llama-2-13b       | 83.22 | 78.02 | 71.03 | 59.31 | 30.73 | 64.46 | 59.77
 | Llama-2-13b-chat  | 80.46 | 70.54 | 62.87 | 63.05 | 25.73 | 60.93 | 51.21
-| SeaLLM-13b-chat-v1 | 83.12 | 73.95 | 74.16 | 61.37 | 60.94 | 70.71 | 65.49
-| SeaLLM-13b-chat-v2 | 81.51 | 76.10 | 73.64 | 69.11 | 64.54 | 72.98 | 69.10
+| SeaLLM-13b-chat   | 75.23 | 75.65 | 72.86 | 64.37 | 61.37 | 69.90	| 66.20
 
 
 #### Translation
@@ -174,12 +170,12 @@ For translation tasks, we evaluate our models with the [FloRes-200](https://gith
 
 Similarly observed, our SeaLLM models outperform Llama-2 significantly in the new languages.
 
+
 | FloRes-200 (chrF++) | En-Zh | En-Vi | En-Id | En-Th | En->X | Zh-En | Vi-En | Id-En | Th-En | X->En
 |-------- | ---- | ---- |  ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | 
-| Llama-2-13b | 24.36 | 53.20 | 60.41 | 22.16 | 45.26 | 53.20 | 59.10 | 63.42 | 38.48 | 53.55
-| Llama-2-13b-chat | 19.58 | 51.70 | 57.14 | 21.18 | 37.40 | 52.27 | 54.32 | 60.55 | 30.18 | 49.33
-| SeaLLM-13b-chat-v1 | 22.77 | 58.96 | 64.78 | 42.38 | 55.37 | 53.20 | 60.29 | 65.03 | 57.24 | 60.85
-| SeaLLM-13b-chat-v2 | 22.75 | 58.78 | 65.90 | 42.60 | 55.76 | 53.34 | 60.80 | 65.44 | 57.05 | 61.10
+| Llama-2-13b       | 24.36 | 53.20 | 60.41 | 22.16 | 45.26 | 53.20 | 59.10 | 63.42 | 38.48 | 53.55
+| Llama-2-13b-chat  | 19.58 | 51.70 | 57.14 | 21.18 | 37.40 | 52.27 | 54.32 | 60.55 | 30.18 | 49.33
+| SeaLLM-13b-chat   | 23.12 | 53.67 | 59.00 | 60.93 | 66.16 | 65.66 | 43.33 | 57.39
 
 Our models are also performing competitively with ChatGPT for translation between SEA languages without English pivoting.
 
@@ -197,7 +193,7 @@ Lastly, in 2-shot [XL-sum summarization tasks](https://aclanthology.org/2021.fin
 |-------- | ---- | ---- |  ---- | ---- | ---- |
 | Llama-2-13b        | 32.57 | 34.37 | 18.61 | 25.14 | 16.91
 | Llama-2-13b-chat   | 25.11 | 31.13 | 18.29 | 22.45 | 17.51
-| SeaLLM-13b-chat-v2 | 27.00 | 33.31 | 20.31 | 25.69 | 21.97
+| SeaLLM-13b-chat    | 26.88 | 33.39 | 19.39 | 25.96 | 21.37
 
 ## Acknowledge our linguists