Update README.md

README.md

@@ -4,6 +4,7 @@ license: apache-2.0
 base_model: samchain/econo-sentence-v2
 tags:
 - generated_from_trainer
+- finance
 metrics:
 - accuracy
 - f1
@@ -12,6 +13,11 @@ metrics:
 model-index:
 - name: EconoSentiment
   results: []
+datasets:
+- FinanceMTEB/financial_phrasebank
+language:
+- en
+pipeline_tag: text-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,7 +25,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # EconoSentiment
 
-This model is a fine-tuned version of [samchain/econo-sentence-v2](https://huggingface.co/samchain/econo-sentence-v2) on an unknown dataset.
+This model is a fine-tuned version of [samchain/econo-sentence-v2](https://huggingface.co/samchain/econo-sentence-v2) on the Financial Phrase Bank dataset from FinanceMTEB.
 It achieves the following results on the evaluation set:
 - Loss: 0.1293
 - Accuracy: 0.962
@@ -29,15 +35,15 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+The base model is a sentence-transformers model built from [EconoBert](https://huggingface.co/samchain/EconoBert).
 
 ## Intended uses & limitations
 
-More information needed
+This model is trained to provide a useful tool for sentiment analysis in finance.
 
 ## Training and evaluation data
 
-More information needed
+The dataset is directly downloaded from the huggingface repo of the FinanceMTEB. The preprocessing consisted of tokenizing to a fixed sequence length of 512 tokens.
 
 ## Training procedure
 
@@ -66,4 +72,4 @@ The following hyperparameters were used during training:
 - Transformers 4.50.0
 - Pytorch 2.1.0+cu118
 - Datasets 3.4.1
-- Tokenizers 0.21.1
+- Tokenizers 0.21.1