Evaluation results for MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli model as a base model for other tasks

As part of a research effort to identify high quality models in Huggingface that can serve as base models for further finetuning, we evaluated this by finetuning on 36 datasets. The model ranks 2nd among all tested models for the microsoft/deberta-v3-base architecture as of 09/01/2023.


To share this information with others in your model card, please add the following evaluation results to your README.md page.

For more information please see https://ibm.github.io/model-recycling/ or contact me.

Best regards,
Elad Venezian
eladv@il.ibm.com
IBM Research AI

README.md

@@ -344,3 +344,17 @@ If you have questions or ideas for cooperation, contact me at m{dot}laurer{at}vu
 
 ### Debugging and issues
 Note that DeBERTa-v3 was released on 06.12.21 and older versions of HF Transformers seem to have issues running the model (e.g. resulting in an issue with the tokenizer). Using Transformers>=4.13 might solve some issues. 
+
+## Model Recycling
+
+[Evaluation on 36 datasets](https://ibm.github.io/model-recycling/model_gain_chart?avg=0.65&mnli_lp=nan&20_newsgroup=-0.61&ag_news=-0.01&amazon_reviews_multi=0.46&anli=0.84&boolq=2.12&cb=16.07&cola=-0.76&copa=8.60&dbpedia=-0.40&esnli=-0.29&financial_phrasebank=-1.98&imdb=-0.47&isear=-0.22&mnli=-0.21&mrpc=0.50&multirc=1.91&poem_sentiment=1.73&qnli=0.07&qqp=-0.37&rotten_tomatoes=-0.74&rte=3.94&sst2=-0.45&sst_5bins=0.07&stsb=1.27&trec_coarse=-0.16&trec_fine=0.18&tweet_ev_emoji=-0.93&tweet_ev_emotion=-1.33&tweet_ev_hate=-1.67&tweet_ev_irony=-5.46&tweet_ev_offensive=-0.17&tweet_ev_sentiment=-0.11&wic=-0.21&wnli=-1.20&wsc=4.18&yahoo_answers=-0.70&model_name=MoritzLaurer%2FDeBERTa-v3-base-mnli-fever-anli&base_name=microsoft%2Fdeberta-v3-base) using MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli as a base model yields average score of 79.69 in comparison to 79.04 by microsoft/deberta-v3-base.
+
+The model is ranked 2nd among all tested models for the microsoft/deberta-v3-base architecture as of 09/01/2023
+Results:
+
+|   20_newsgroup |   ag_news |   amazon_reviews_multi |   anli |   boolq |      cb |    cola |   copa |   dbpedia |   esnli |   financial_phrasebank |   imdb |   isear |    mnli |    mrpc |   multirc |   poem_sentiment |   qnli |     qqp |   rotten_tomatoes |     rte |    sst2 |   sst_5bins |    stsb |   trec_coarse |   trec_fine |   tweet_ev_emoji |   tweet_ev_emotion |   tweet_ev_hate |   tweet_ev_irony |   tweet_ev_offensive |   tweet_ev_sentiment |     wic |    wnli |     wsc |   yahoo_answers |
+|---------------:|----------:|-----------------------:|-------:|--------:|--------:|--------:|-------:|----------:|--------:|-----------------------:|-------:|--------:|--------:|--------:|----------:|-----------------:|-------:|--------:|------------------:|--------:|--------:|------------:|--------:|--------------:|------------:|-----------------:|-------------------:|----------------:|-----------------:|---------------------:|---------------------:|--------:|--------:|--------:|----------------:|
+|        85.8072 |   90.4333 |                  67.32 | 59.625 |  85.107 | 91.0714 | 85.8102 |     67 |   79.0333 | 91.6327 |                   82.5 |  94.02 | 71.6428 | 89.5749 | 89.7059 |   64.1708 |          88.4615 | 93.575 | 91.4148 |           89.6811 | 86.2816 | 94.6101 |     57.0588 | 91.5508 |          97.6 |        91.2 |           45.264 |            82.6179 |         54.5455 |          74.3622 |              84.8837 |              71.6949 | 71.0031 | 69.0141 | 68.2692 |         71.3333 |
+
+
+For more information, see: [Model Recycling](https://ibm.github.io/model-recycling/)