.ipynb files
csv files.py files
training.py contains Trainer class to train BertForSequenceClassificationprediction.py contains Predictor class to predict sentiments from text data using pre trained modelmetrics.py contains functions to compute precision, recall, and f1 scoresevaluation.py contains a function to evaluate pre trained model using test datainput_data_preprocessing.py contains utility function to fix initial csv files| Positive | Neutral | Negative | Average | |
|---|---|---|---|---|
| Precision | 0.744 | 0.717 | 0.799 | 0.753 |
| Recall | 0.811 | 0.623 | 0.833 | 0.756 |
| F1 | 0.776 | 0.667 | 0.816 | 0.753 |
7 commits
Jupyter Notebook
84.8%
Python
15.2%
.ipynb files
csv files.py files
training.py contains Trainer class to train BertForSequenceClassificationprediction.py contains Predictor class to predict sentiments from text data using pre trained modelmetrics.py contains functions to compute precision, recall, and f1 scoresevaluation.py contains a function to evaluate pre trained model using test datainput_data_preprocessing.py contains utility function to fix initial csv files| Positive | Neutral | Negative | Average | |
|---|---|---|---|---|
| Precision | 0.744 | 0.717 | 0.799 | 0.753 |
| Recall | 0.811 | 0.623 | 0.833 | 0.756 |
| F1 | 0.776 | 0.667 | 0.816 | 0.753 |
7 commits
Jupyter Notebook
84.8%
Python
15.2%