Update README.md

README.md

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+---
+language: 
+- en
+thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
+tags:
+- text-classification
+- emotion
+- pytorch
+license: apache-2.0
+datasets:
+- emotion
+metrics:
+- Accuracy, F1 Score
+---
+# bert-base-uncased-emotion
+
+## Model description:
+`bert-base-uncased` finetuned on the emotion dataset using HuggingFace Trainer.
+```
+ learning rate 2e-5, 
+ batch size 64,
+ num_train_epochs=8,
+```
+
+## How to Use the model:
+```python
+from transformers import pipeline
+classifier = pipeline("sentiment-analysis",model='bhadresh-savani/bert-base-uncased-emotion')
+prediction = classifier("I love using transformers. The best part is wide range of support and its easy to use")
+```
+
+## Dataset:
+[Twitter-Sentiment-Analysis](https://huggingface.co/nlp/viewer/?dataset=emotion).
+
+## Training procedure
+[Colab Notebook](https://github.com/bhadreshpsavani/ExploringSentimentalAnalysis/blob/main/SentimentalAnalysisWithDistilbert.ipynb)
+
+## Eval results
+```
+{
+ 'test_accuracy': 0.9355,
+ 'test_f1': 0.9354074792391709,
+ 'test_loss': 0.18557891249656677,
+ 'test_runtime': 11.0092,
+ 'test_samples_per_second': 181.666,
+ 'test_steps_per_second': 2.907
+ }
+```