Update README.md

README.md

@@ -13,7 +13,7 @@ base_model:
 
 Tiny Language Model For Japanese and English Bidirectional Translation
 
-- **Purrs on your lap** 🐱: Small and efficient! 0.8-3.3B models that run on edge devices.
+- **Purrs on your lap** 🐱: Small and efficient! 0.8-7B models that run on edge devices.
 - **Swift and Feline Sharp** 🐾: Beats TranslateGemma-12B on text-to-text translation quality.
 - **Adopt and adapt** 🐈: Open source (MIT License) models you can customize and extend.
 
@@ -28,6 +28,7 @@ All models are available on Hugging Face:
 - [CAT-Translate-0.8B](https://huggingface.co/cyberagent/CAT-Translate-0.8b/)
 - [CAT-Translate-1.4B](https://huggingface.co/cyberagent/CAT-Translate-1.4b/)
 - [CAT-Translate-3.3B](https://huggingface.co/cyberagent/CAT-Translate-3.3b/)
+- [CAT-Translate-7B](https://huggingface.co/cyberagent/CAT-Translate-7b/)
 
 ## Evaluation
 
@@ -44,22 +45,24 @@ We conducted evaluation on the translation subsets of the following benchmarks:
 We chose these tasks as benchmarks because (1) they are derived from real world applications and (2) are less overoptimized compared to popular datasets (e.g., WMT).
 
 The results are below.
-Overall, our 1.4B model achieved the best overall scores.
-The 0.8B, 1.4B, and 3.3B-beta models achieved the best scores among all models (including closed source) within their respective sizes for both En-Ja and Ja-En translation tasks.
+All the models achieved the best scores among all models (including closed source) within their respective sizes for both En-Ja and Ja-En translation tasks.
 
 
 | Model                                            | Avg. BLEU | Avg. BLEU Ja->En | Avg. BLEU En->Ja | BSD (Ja-En) | Court (Ja-En) | JMed (Ja-En) | PFMT (Ja-En) | wat-pat-2025 (Ja-En) | BSD (En-Ja) | JMed (En-Ja) | PFMT (En-Ja) | wat-pat-2025 (En-Ja) |
 |:-------------------------------------------------|----------:|-----------------:|-----------------:|------------:|--------------:|-------------:|-------------:|------------------:|------------:|-------------:|-------------:|------------------:|
+| CyberAgent/CAT-Translate-7B                       |   37.68  |   41.06  |   34.31  |  33.75  |  45.29  |  30.65  |  49.86  |  45.74  |  16.29  |  29.62  |  52.94  |  38.37  |
+| CyberAgent/CAT-Translate-3.3B                       |   36.16  |   37.51  |   34.80  |  26.51  |  42.44  |  24.47  |  49.93  |  44.23  |  17.21  |  28.67  |  53.88  |  39.44  |
 | CyberAgent/CAT-Translate-1.4B                      |   33.73  |   33.26  |   34.19  |  31.28  |  43.84  |  24.08  |  36.55  |  30.57  |  15.71  |  26.92  |  51.53  |  42.58  |
 | Unbabel/Tower-Plus-9B                              |   32.41  |   36.84  |   27.99  |  15.43  |  40.54  |  29.13  |  58.00  |  41.10  |  10.00  |  18.80  |  53.00  |  30.16  |
 | google/translategemma-12b-it                       |   32.24  |   35.81  |   28.68  |  31.58  |  34.30  |  23.46  |  48.75  |  40.97  |  15.92  |  21.79  |  52.53  |  24.47  |
-| CyberAgent/CAT-Translate-3.3B                 |   30.60  |   30.32  |   30.88  |  17.20  |  38.65  |  23.96  |  40.58  |  31.22  |  16.63  |  26.68  |  53.40  |  26.80  |
+| CyberAgent/CAT-Translate-3.3B-beta               |   30.60  |   30.32  |   30.88  |  17.20  |  38.65  |  23.96  |  40.58  |  31.22  |  16.63  |  26.68  |  53.40  |  26.80  |
 | CyberAgent/CAT-Translate-0.8B                    |   30.42  |   29.71  |   30.68  |  29.63  |  33.19  |  22.96  |  32.51  |  30.56  |  14.60  |  26.22  |  50.62  |  32.87  |
 | google/translategemma-4b-it                      |   28.09  |   29.41  |   26.76  |  28.86  |  25.89  |  21.50  |  42.65  |  28.16  |  14.14  |  20.68  |  51.99  |  20.23  |
 | LiquidAI/LFM2.5-1.2B-JP                          |   25.47  |   24.51  |   26.43  |  19.06  |  29.99  |  22.10  |  43.61  |   7.80  |  14.57  |  23.85  |  54.77  |  12.54  |
 | pfnet/plamo-2-translate                          |   25.24  |   25.92  |   24.57  |  25.55  |  28.63  |  22.90  |  29.02  |  23.48  |  17.35  |  24.98  |  32.04  |  23.89  |
 | LiquidAI/LFM2-350M-ENJP-MT                       |   24.95  |   24.91  |   25.00  |  10.94  |  29.56  |  21.48  |  41.40  |  21.17  |   8.11  |  22.84  |  47.53  |  21.52  |
 | mistralai/Ministral-8B-Instruct-2410             |   24.12  |   27.52  |   20.71  |  19.23  |  29.21  |  16.25  |  50.23  |  22.69  |  12.91  |  16.49  |  41.66  |  11.80  |
+| nvidia/NVIDIA-Nemotron-Nano-9B-v2-Japanese      |   22.97  |   22.77  |   23.18  |   9.62  |  34.98  |  18.01  |  38.44  |  12.81  |  10.62  |  20.41  |  42.55  |  19.13  |
 | Rakuten/RakutenAI-2.0-mini-instruct              |   18.43  |   17.24  |   19.62  |   0.11  |  30.62  |  18.21  |  29.34  |   7.90  |   5.19  |  20.36  |  45.70  |   7.23  |
 | SakanaAI/TinySwallow-1.5B-Instruct               |   15.74  |   14.99  |   16.49  |   4.96  |  18.93  |  15.83  |  26.67  |   8.58  |   6.30  |  17.58  |  34.07  |   8.00  |
 | llm-jp/llm-jp-3.1-1.8b-instruct4                 |   15.18  |   16.26  |   14.11  |  18.82  |   2.44  |  15.67  |  30.65  |  13.72  |  15.38  |   4.91  |  25.47  |  10.65  |