Update README.md

README.md

@@ -27,13 +27,14 @@ OpenLLM-Ro represents the first open-source effort to build a LLM specialized fo
 - **Language(s):** Romanian
 - **License:** cc-by-nc-4.0
 - **Finetuned from model:** [gemma-7b](https://huggingface.co/google/gemma-7b)
+- **Trained using:** [RoAlpaca](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_alpaca), [RoAlpacaGPT4](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_alpaca_gpt4), [RoDolly](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_dolly), [RoSelfInstruct](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_selfinstruct_gpt4), [RoNoRobots](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_norobots), [RoOrca](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_orca), [RoCamel](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_camel)
 
 
 ### Model Sources
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** https://github.com/OpenLLM-Ro/llama-recipes
+- **Repository:** https://github.com/OpenLLM-Ro/LLaMA-Factory
 - **Paper:** https://arxiv.org/abs/2406.18266
 
 ## Intended Use
@@ -71,28 +72,138 @@ outputs = model.generate(input_ids=inputs, max_new_tokens=128)
 print(tokenizer.decode(outputs[0]))
 ```
 
-## Benchmarks
-
-| Model              | Average  | ARC      | MMLU     |Winogrande|HellaSwag | GSM8k    |TruthfulQA|
-|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
-| google/gemma-1.1-7b-it| 41.39    | 40.05    | 47.12    | 54.62    | 47.10    | 9.73    | 49.75    |  
-| *RoGemma-7b-Instruct*  | ***53.65***    | ***52.77***    | ***54.69***    | ***69.10***    | ***61.97***    | ***31.97***     | ***51.43***   |  
+## Academic Benchmarks
+
+<table>
+<tbody>
+<tr>
+<td><strong>Model</strong></td>
+<td><strong><center>Average</center></strong></td>
+<td><strong><center>ARC</center></strong></td>
+<td><strong><center>MMLU</center></strong></td>
+<td><strong><center>Winogrande</center></strong></td>
+<td><strong><center>Hellaswag</center></strong></td>
+<td><strong><center>GSM8k</center></strong></td>
+<td><strong><center>TruthfulQA</center></strong></td>
+</tr>
+<tr>
+<td>gemma-1.1-7b-it</td><td><center>41.44</center></td><td><center>40.32</center></td><td><center>47.22</center></td><td><center>55.01</center></td><td><center>47.03</center></td><td><center>9.50</center></td><td><center>49.58</center></td>
+</tr>
+<tr>
+<td><em>RoGemma-7b-Instruct</em></td><td><center><em><strong>53.42</strong></em></center></td><td><center><em><strong>52.44</strong></em></center></td><td><center><em><strong>54.44</strong></em></center></td><td><center><em><strong>69.36</strong></em></center></td><td><center><em><strong>61.96</strong></em></center></td><td><center><em><strong>31.06</strong></em></center></td><td><center><em><strong>51.23</strong></em></center></td>
+</tr>
+</tbody>
+</table>
+
+## Downstream tasks
+
+<table>
+<tbody>
+<tr>
+<td></td>
+<td colspan="4"><center><strong>LaRoSeDa</strong></center></td>
+<td colspan="4"><center><strong>WMT</strong></center></td>
+</tr>
+<tr>
+<td></td>
+<td colspan="2"><center><strong>Few-shot</strong></center></td>
+<td colspan="2"><center><strong>Finetuned</strong></center></td>
+<td colspan="2"><center><strong>Few-shot</strong></center></td>
+<td colspan="2"><center><strong>Finetuned</strong></center></td>
+</tr>
+<tr>
+<td><strong>Model</strong></td>
+<td><center><strong>Binary<br>(Macro F1)</strong></center></td>
+<td><center><strong>Multiclass<br>(Macro F1)</strong></center></td>
+<td><center><strong>Binary<br>(Macro F1)</strong></center></td>
+<td><center><strong>Multiclass<br>(Macro F1)</strong></center></td>
+<td><center><strong>EN-RO<br>(Bleu)</strong></center></td>
+<td><center><strong>RO-EN<br>(Bleu)</strong></center></td>
+<td><center><strong>EN-RO<br>(Bleu)</strong></center></td>
+<td><center><strong>RO-EN<br>(Bleu)</strong></center>
+</tr>
+<tr>
+<td>gemma-1.1-7b-it</td><td><center>87.54</center></td><td><center>51.49</center></td><td><center>83.87</center></td><td><center>85.61</center></td><td><center>17.96</center></td><td><center><strong>27.74</strong></center></td><td><center>25.48</center></td><td><center>36.11</center></td>
+</tr>
+<tr>
+<td><em>RoGemma-7b-Instruct</em></td><td><center><em><strong>97.87</strong></em></center></td><td><center><em><strong>65.71</strong></em></center></td><td><center><em><strong>98.43</strong></em></center></td><td><center><em><strong>87.18</strong></em></center></td><td><center><em><strong>27.91</strong></em></center></td><td><center><em>23.08</em></center></td><td><center><em><strong>27.99</strong></em></center></td><td><center><em><strong>39.51</strong></em></center></td>
+</tr>
+</tbody>
+</table>
+
+
+<table>
+<tbody>
+<tr>
+<td></td>
+<td colspan="4"><center><strong>XQuAD</strong></center></td>
+<td colspan="4"><center><strong>STS</strong></center></td>
+</tr>
+<tr>
+<td></td>
+<td colspan="2"><center><strong>Few-shot</strong></center></td>
+<td colspan="2"><center><strong>Finetuned</strong></center></td>
+<td colspan="2"><center><strong>Few-shot</strong></center></td>
+<td colspan="2"><center><strong>Finetuned</strong></center></td>
+</tr>
+<tr>
+<td><strong>Model</strong></td>
+<td><center><strong>(EM)</strong></center></td>
+<td><center><strong>(F1)</strong></center></td>
+<td><center><strong>(EM)</strong></center></td>
+<td><center><strong>(F1)</strong></center></td>
+<td><center><strong>(Spearman)</strong></center></td>
+<td><center><strong>(Pearson)</strong></center></td>
+<td><center><strong>(Spearman)</strong></center></td>
+<td><center><strong>(Pearson)</strong></center></td>
+</tr>
+<tr>
+<td>gemma-1.1-7b-it</td><td><center><strong>42.10</strong></center></td><td><center><strong>62.30</strong></center></td><td><center><strong>60.34</strong></center></td><td><center><strong>77.40</strong></center></td><td><center>49.10</center></td><td><center>50.23</center></td><td><center>83.43</center></td><td><center>83.65</center></td>
+</tr>
+<tr>
+<td><em>RoGemma-7b-Instruct</em></td><td><center><em>17.75</em></center></td><td><center><em>28.11</em></center></td><td><center><em>52.02</em></center></td><td><center><em>68.43</em></center></td><td><center><em><strong>73.96</strong></em></center></td><td><center><em><strong>75.16</strong></em></center></td><td><center><em><strong>86.45</strong></em></center></td><td><center><em><strong>86.31</strong></em></center></td>
+</tr>
+</tbody>
+</table>
 
 
 ## MT-Bench
 
-| Model              | Average  | 1st turn      | 2nd turn     | Answers in Ro |
-|--------------------|:--------:|:--------:|:--------:|:--------:|
-| google/gemma-1.1-7b-it    | 4.63    | 5.18    | 4.08    | **160 / 160**|
-| *RoGemma-7b-Instruct*| ***4.83***|***5.56***| ***4.10*** |**160 / 160**|
+<table>
+<tbody>
+<tr>
+<td><strong>Model</strong></td>
+<td><strong><center>Average</center></strong></td>
+<td><strong><center>1st turn</center></strong></td>
+<td><strong><center>2nd turn</center></strong></td>
+<td><strong><center>Answers in Ro</center></strong></td>
+</tr>
+<tr>
+<td>gemma-1.1-7b-it</td><td><center>4.83</center></td><td><center>5.11</center></td><td><center>4.55</center></td><td><center><strong>160/160</strong></center></td>
+</tr>
+<tr>
+<td><em>RoGemma-7b-Instruct</em></td><td><center><em><strong>5.26</strong></em></center></td><td><center><em><strong>5.92</strong></em></center></td><td><center><em><strong>4.60</strong></em></center></td><td><center><em><strong>160/160</strong></em></center></td>
+</tr>
+</tbody>
+</table>
 
 ## RoCulturaBench
 
-| Model              | Score  | Answers in Ro|
-|--------------------|:--------:|:--------:|
-| google/gemma-1.1-7b-it   | **3.22**    | **100 / 100**  |
-| *RoGemma-7b-Instruct*| *3.47*| ***100 / 100*** |
-
+<table>
+<tbody>
+<tr>
+<td><strong>Model</strong></td>
+<td><strong><center>Average</center></strong></td>
+<td><strong><center>Answers in Ro</center></strong></td>
+</tr>
+<tr>
+<td>gemma-1.1-7b-it</td><td><center><strong>3.38</strong></center></td><td><center><strong>100/100</strong></center></td>
+</tr>
+<tr>
+<td><em>RoGemma-7b-Instruct</em></td><td><center><em>3.26</em></center></td><td><center><em><strong>100/100</strong></em></center></td>
+</tr>
+</tbody>
+</table>
 
 
 ## RoGemma Model Family