PyTorch Text Model Builder
1. Model Configuration
2. Data Preprocessing
3. Training & Evaluation
4. Visualizations
1. Configure Your Model
Model Architecture:
LSTM
GRU
Transformer
Text Embedding Method:
Word2Vec
GloVe
FastText
Learning Rate:
Epochs:
Batch Size:
Random Seed:
Enable GPU for Training
Save Configuration
2. Upload & Preprocess Data
Select Popular Dataset (Optional):
-- Select a dataset --
IMDB Sentiment
AG News
Spam Email Classification
OR
Upload Your Own Dataset (CSV, TXT):
No file selected
Tokenization Method:
NLTK
spaCy
Hugging Face Tokenizer
Remove Stop Words
Apply Stemming
Preview Preprocessed Data
Run Preprocessing
Data Preview:
3. Model Training & Evaluation
Start Training
Stop Training
Training Status:
Idle
0%
Complete
Current Epoch:
N/A
Current Loss:
N/A
Current Accuracy:
N/A
Error:
4. Training Visualizations
Training Loss & Accuracy Over Epochs
Confusion Matrix (Classification Tasks)
Word Cloud (Frequent Terms)
Generate data to see word cloud (e.g., by completing preprocessing and training).