Update README.md

README.md

@@ -51,6 +51,19 @@ All pre-training is done on the [Cultura-X](https://huggingface.co/datasets/uonl
 ## Tokenizer Details
 We extended the vocabulary of the base llama model from 32,000 tokens to 57,000 tokens by adding up to 25,000 non-overlapping tokens from the new language.
 
+## Evaluation
+|| SambaLingo-Japanese-Base     | ELYZA-japanese-Llama-2-7b-7b | bloom-7b1 | xglm-7.5B | mGPT-13B |        
+|------------------------------|------------------------------|-----------|-----------|----------|--------|
+| Perplexity (Lower Is Better) | 1.559                        | 1.754     | 2.216     | 1.775    | 2.349  |
+| FLORES en->ja (8 shot, CHRF) | 0.281                        | 0.250     | 0.056     | 0.156    | 0.111  |
+| FLORES ja->en (8 shot, CHRF) | 0.495                        | 0.436     | 0.262     | 0.369    | 0.297  |
+| FLORES en->ja (8 shot, BLEU) | 0.000                        | 0.000     | 0.000     | 0.000    | 0.000  |
+| FLORES ja->en (8 shot, BLEU) | 0.184                        | 0.144     | 0.043     | 0.084    | 0.036  |
+| Belebele (3 shot)            | 36.56%                       | 53.67%    | 26.67%    | 24.00%   | 22.89% |
+| SIB-200 (3 shot)             | 68.63%                       | 74.02%    | 60.29%    | 60.78%   | 41.18% |
+| PAWS-X                       | 46.80%                       | 50.50%    | 45.40%    | 51.95%   | 45.20% |
+| XWinograd (0 shot)           | 76.64%                       | 77.58%    | 58.92%    | 64.96%   | 57.77% |
+
 ## Uses
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->