ai-sa-r002

.gitattributes

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README.md

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 ---
 license: apache-2.0
-thumbnail: https://huggingface.co/mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis/resolve/main/logo_no_bg.png
 tags:
 - generated_from_trainer
 - financial
@@ -31,32 +30,24 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-
-<div style="text-align:center;width:250px;height:250px;">
-    <img src="https://huggingface.co/mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis/resolve/main/logo_no_bg.png" alt="logo">
-</div>
-
-
-# DistilRoberta-financial-sentiment
-
+# distilRoberta-financial-sentiment
 
 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the financial_phrasebank dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.1116
-- Accuracy: **0.98**23
+- Accuracy: 0.9823
+
+## Model description
 
-## Base Model description
+More information needed
 
-This model is a distilled version of the [RoBERTa-base model](https://huggingface.co/roberta-base). It follows the same training procedure as [DistilBERT](https://huggingface.co/distilbert-base-uncased).
-The code for the distillation process can be found [here](https://github.com/huggingface/transformers/tree/master/examples/distillation).
-This model is case-sensitive: it makes a difference between English and English.
+## Intended uses & limitations
 
-The model has 6 layers, 768 dimension and 12 heads, totalizing 82M parameters (compared to 125M parameters for RoBERTa-base).
-On average DistilRoBERTa is twice as fast as Roberta-base.
+More information needed
 
-## Training Data
+## Training and evaluation data
 
-Polar sentiment dataset of sentences from financial news. The dataset consists of 4840 sentences from English language financial news categorised by sentiment. The dataset is divided by agreement rate of 5-8 annotators.
+More information needed
 
 ## Training procedure
 

model.safetensors

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