DILAB-HYU
/

KoQuality-Polyglot-5.8b

@@ -7,32 +7,36 @@ license: cc-by-4.0
 KoQuality-Polyglot-5.8b is a fine-tuned version of [EleutherAI/polyglot-ko-5.8b](https://huggingface.co/EleutherAI/polyglot-ko-5.8b) on [KoQuality dataset](https://huggingface.co/datasets/DILAB-HYU/KoQuality), which is curated by proposed method (len_group=5, k=100, n=0.01, method=ppl_sampling).
-### Overall Average accuracy score of the KoBEST datasets
 We use [KoBEST benchmark](https://huggingface.co/datasets/skt/kobest_v1) datasets(BoolQ, COPA, HellaSwag, SentiNeg, WiC) to compare the performance of our best model and other models accuracy. Our model outperforms other models in the average accuracy score of the KoBEST datasets.
 <img src=https://cdn-uploads.huggingface.co/production/uploads/650fecfd247f564485f8fbcf/q4cCUCzRJa3m2f7oxI_FY.png style="max-width: 500px; width: 300%"/>
 | Model | 0-shot | 1-shot | 2-shot | 5-shot | 10-shot
 | --- | --- | --- | --- | --- | --- |
-| koquality-polyglot-5.8b | 0.5472 | 0.5979 | 0.6260 | 0.6486 | 0.6535
 | polyglot-ko-5.8b | 0.5587 | 0.5977 | 0.6138 | 0.6431 | 0.6457
 | koalpcaca-polyglot-5.8b | 0.5085 | 0.5561 | 0.5768 | 0.6097 | 0.6059
 | kullm-polyglot-5.8b | 0.5409 | 0.6072 | 0.5945 | 0.6345 | 0.6530
-### Evaluation results
-COPA (F1)
 <img src=https://cdn-uploads.huggingface.co/production/uploads/650fecfd247f564485f8fbcf/7EKl1OAgKgPBFcSlGzBiW.png style="max-width: 800px; width: 400%"/>
-HellaSwag (F1)
-BoolQ (F1)
-SentiNeg (F1)
-WiC (F1)
@@ -48,10 +52,10 @@ WiC (F1)
 - num_epochs: 2.0
 ## Framework versions
-Transformers 4.30.2
-Pytorch 2.0.1+cu117
-Datasets 2.11.0
-deepspeed 0.9.5
 ## Citation

 KoQuality-Polyglot-5.8b is a fine-tuned version of [EleutherAI/polyglot-ko-5.8b](https://huggingface.co/EleutherAI/polyglot-ko-5.8b) on [KoQuality dataset](https://huggingface.co/datasets/DILAB-HYU/KoQuality), which is curated by proposed method (len_group=5, k=100, n=0.01, method=ppl_sampling).
+## Overall Average accuracy score of the KoBEST datasets
 We use [KoBEST benchmark](https://huggingface.co/datasets/skt/kobest_v1) datasets(BoolQ, COPA, HellaSwag, SentiNeg, WiC) to compare the performance of our best model and other models accuracy. Our model outperforms other models in the average accuracy score of the KoBEST datasets.
 <img src=https://cdn-uploads.huggingface.co/production/uploads/650fecfd247f564485f8fbcf/q4cCUCzRJa3m2f7oxI_FY.png style="max-width: 500px; width: 300%"/>
 | Model | 0-shot | 1-shot | 2-shot | 5-shot | 10-shot
 | --- | --- | --- | --- | --- | --- |
 | polyglot-ko-5.8b | 0.5587 | 0.5977 | 0.6138 | 0.6431 | 0.6457
 | koalpcaca-polyglot-5.8b | 0.5085 | 0.5561 | 0.5768 | 0.6097 | 0.6059
 | kullm-polyglot-5.8b | 0.5409 | 0.6072 | 0.5945 | 0.6345 | 0.6530
+| koquality-polyglot-5.8b | 0.5472 | 0.5979 | 0.6260 | 0.6486 | 0.6535
+## Evaluation results
+### COPA (F1)
 <img src=https://cdn-uploads.huggingface.co/production/uploads/650fecfd247f564485f8fbcf/7EKl1OAgKgPBFcSlGzBiW.png style="max-width: 800px; width: 400%"/>
+| Model | 0-shot | 1-shot | 2-shot | 5-shot | 10-shot
+| --- | --- | --- | --- | --- | --- |
+| polyglot-ko-5.8b | 0.5587 | 0.5977 | 0.6138 | 0.6431 | 0.6457
+| koalpcaca-polyglot-5.8b | 0.5085 | 0.5561 | 0.5768 | 0.6097 | 0.6059
+| kullm-polyglot-5.8b | 0.5409 | 0.6072 | 0.5945 | 0.6345 | 0.6530
+| koquality-polyglot-5.8b | 0.5472 | 0.5979 | 0.6260 | 0.6486 | 0.6535
+### HellaSwag (F1)
+### BoolQ (F1)
+### SentiNeg (F1)
+### WiC (F1)
 - num_epochs: 2.0
 ## Framework versions
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.11.0
+- deepspeed 0.9.5
 ## Citation