Merge branch 'main' of https://huggingface.co/krishnagarg09/stance-detection-semeval2016 into main

README.md

@@ -1,75 +1,3 @@
-# Model Card for krishnagarg09/stance-detection-semeval2016
-
-## Model Description
-The goal is to identify the stance (AGAINST, NONE, FAVOR) of a user towards a given target.
-
-Sample:
-
-```
-Input: Lord, You are my Hope! In You I will always trust.
-Target: Atheism
-Stance: AGAINST
-```
-
-The model is pretrained on SemEval2016-Task6 stance detection dataset. The dataset is available  at https://huggingface.co/datasets/krishnagarg09/SemEval2016Task6.
-
-Ref: https://aclanthology.org/S16-1003/ for more details about the dataset
-
-- **Developed by:** Krishna Garg
-- **Shared by [Optional]:** Krishna Garg
-- **Model type:** Language model
-- **Language(s) (NLP):** en
-- **License:** mit
-- **Resources for more information:**
-    - [Associated Paper](https://aclanthology.org/S16-1003/)
-
-## Direct Use
-```
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-from datasets import load_dataset
-
-# load model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("krishnagarg09/stance-detection-semeval2016")
-model = AutoModelForSequenceClassification.from_pretrained("krishnagarg09/stance-detection-semeval2016")
-
-# load dataset
-dataset = load_dataset("krishnagarg09/SemEval2016Task6")
-
-# prepare input
-text = dataset['test']['Tweet']
-encoded_input = tokenizer(text, return_tensors='pt', add_special_tokens = True, max_length=128, padding=True, truncation=True)
-
-# forward pass
-output = model(**encoded_input)
-```
-
-## Dataset
-The dataset is available  at https://huggingface.co/datasets/krishnagarg09/SemEval2016Task6.
-```
-dataset = load_dataset("krishnagarg09/SemEval2016Task6")
-```
-
-## Training Details
-optimizer: Adam
-lr: 2e-5
-loss: crossentropy
-epochs: 5 (best weights chosen over validation)
-batch_size: 32
-
-### Preprocessing
-Text lowercased, `#semst` tags removed, `p.OPT.URL,p.OPT.EMOJI,p.OPT.RESERVED` removed using `tweet-preprocessor` package, normalization done using `emnlp_dict.txt` and `noslang_data.json`
-
-## Evaluation
-Evaluation for Stance Detection is done only for 2/3 labels, i.e., FAVOR and AGAINST.
-
-```
-Precision: 62.69
-Recall: 69.43
-F1: 65.56
-```
-
-## Hardware
-Nvidia RTX A5000 24GB
-
-## Model Card Contact
-[email protected]
+---
+license: mit
+---