Update README.md

README.md

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 # Model Card for Model ID
 
-jasmeeetsingh/twitter-depression-classification-sentiment140 is a deep learning model trained to classify whether a given tweet is related to depression or not. 
-The model is based on a transformer architecture and fine-tuned on a large corpus of tweets annotated as depressive or non-depressive.
+jasmeeetsingh/twitter-depression-classification-sentiment140 is a deep learning model trained to classify whether a given tweet is suicidal or not. 
+The model is based on a transformer architecture and fine-tuned on a large corpus of tweets annotated as suicidal or non-suicidal.
 ## Model Details
 
 ### Model Description
@@ -30,39 +30,9 @@ The model is based on a transformer architecture and fine-tuned on a large corpu
 ## Uses
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-The model is intended to be used to classify tweets automatically as depressive or non-depressive. 
+The model is intended to be used to classify tweets automatically as suicidal or non-suicidal. 
 It can be used to analyze large volumes of tweets and identify users who may be at risk of depression, as well as to monitor the prevalence of depression-related discussions on social media platforms.
 
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure 
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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-#### Preprocessing [optional]
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-[More Information Needed]
-
-
-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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-#### Speeds, Sizes, Times [optional]
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-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
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-## Evaluation
-
 <!-- This section describes the evaluation protocols and provides the results. -->
 
 #### Metrics
@@ -70,6 +40,6 @@ It can be used to analyze large volumes of tweets and identify users who may be
 
 
 ## Technical Specifications
-Model was trained on a 6GB RTX 3060
+The model was trained on a 6GB RTX 3060