bert-model-intent-classification
This model is a fine-tuned version of
bert-base-uncased on the None dataset.
Model description
We have finetuned Base Bert model for text classification task. We used intent-detection dataset for traning our model.
Intended uses & limitations
More information needed
How to use
Use below code to test the model
new_model = AutoModelForSequenceClassification.from_pretrained("ArunAIML/bert-model-intent-classification",
num_labels=21,
id2label=id_to_label,
label2id=label_to_id)
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Label Maps used
id_to_labels =
{0: '100_NIGHT_TRIAL_OFFER', 1: 'ABOUT_SOF_MATTRESS', 2: 'CANCEL_ORDER', 3: 'CHECK_PINCODE', 4: 'COD', 5: 'COMPARISON', 6: 'DELAY_IN_DELIVERY', 7: 'DISTRIBUTORS', 8: 'EMI', 9: 'ERGO_FEATURES', 10: 'LEAD_GEN', 11: 'MATTRESS_COST', 12: 'OFFERS', 13: 'ORDER_STATUS', 14: 'ORTHO_FEATURES', 15: 'PILLOWS', 16: 'PRODUCT_VARIANTS', 17: 'RETURN_EXCHANGE', 18: 'SIZE_CUSTOMIZATION', 19: 'WARRANTY', 20: 'WHAT_SIZE_TO_ORDER'}
labels_to_id =
{'100_NIGHT_TRIAL_OFFER': 0, 'ABOUT_SOF_MATTRESS': 1, 'CANCEL_ORDER': 2, 'CHECK_PINCODE': 3, 'COD': 4, 'COMPARISON': 5, 'DELAY_IN_DELIVERY': 6, 'DISTRIBUTORS': 7, 'EMI': 8, 'ERGO_FEATURES': 9, 'LEAD_GEN': 10, 'MATTRESS_COST': 11, 'OFFERS': 12, 'ORDER_STATUS': 13, 'ORTHO_FEATURES': 14, 'PILLOWS': 15, 'PRODUCT_VARIANTS': 16, 'RETURN_EXCHANGE': 17, 'SIZE_CUSTOMIZATION': 18, 'WARRANTY': 19, 'WHAT_SIZE_TO_ORDER': 20}
Please use above labels to reproduce results
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
Results
The model was evaluated on a validation set. Below is the detailed classification report in a tabular format:
| Label | Precision | Recall | F1-Score | Support |
|---|
100_NIGHT_TRIAL_OFFER | 1.00 | 1.00 | 1.00 | 4 |
ABOUT_SOF_MATTRESS | 1.00 | 1.00 | 1.00 | 2 |
CANCEL_ORDER | 1.00 | 1.00 | 1.00 | 2 |
CHECK_PINCODE | 1.00 | 1.00 | 1.00 | 2 |
COD | 1.00 | 1.00 | 1.00 | 2 |
COMPARISON | 0.33 | 0.50 | 0.40 | 2 |
DELAY_IN_DELIVERY | 1.00 | 1.00 | 1.00 | 2 |
DISTRIBUTORS | 1.00 | 1.00 | 1.00 | 7 |
EMI | 0.89 | 1.00 | 0.94 | 8 |
ERGO_FEATURES | 1.00 | 1.00 | 1.00 | 2 |
LEAD_GEN | 1.00 | 1.00 | 1.00 | 4 |
MATTRESS_COST | 1.00 | 0.80 | 0.89 | 5 |
OFFERS | 1.00 | 1.00 | 1.00 | 2 |
ORDER_STATUS | 1.00 | 0.75 | 0.86 | 4 |
ORTHO_FEATURES | 1.00 | 1.00 | 1.00 | 4 |
PILLOWS | 1.00 | 1.00 | 1.00 | 2 |
PRODUCT_VARIANTS | 0.50 | 0.50 | 0.50 | 4 |
RETURN_EXCHANGE | 1.00 | 0.67 | 0.80 | 3 |
SIZE_CUSTOMIZATION | 0.50 | 0.50 | 0.50 | 2 |
WARRANTY | 0.67 | 1.00 | 0.80 | 2 |
WHAT_SIZE_TO_ORDER | 0.80 | 1.00 | 0.89 | 4 |
| Accuracy | | | 0.89 | 66 |
| Macro Avg | 0.90 | 0.89 | 0.89 | 66 |
| Weighted Avg | 0.91 | 0.89 | 0.90 | 66 |
