metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_fine_tunned_flipkart
results: []
token_fine_tunned_flipkart
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0992
- Precision: 0.9526
- Recall: 0.9669
- F1: 0.9597
- Accuracy: 0.9730
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 135 | 0.5967 | 0.7227 | 0.7830 | 0.7516 | 0.7932 |
| No log | 2.0 | 270 | 0.3673 | 0.8105 | 0.8623 | 0.8356 | 0.8747 |
| No log | 3.0 | 405 | 0.2679 | 0.8676 | 0.8854 | 0.8764 | 0.9094 |
| 0.6219 | 4.0 | 540 | 0.1972 | 0.8955 | 0.9217 | 0.9084 | 0.9355 |
| 0.6219 | 5.0 | 675 | 0.1500 | 0.9229 | 0.9374 | 0.9301 | 0.9525 |
| 0.6219 | 6.0 | 810 | 0.1240 | 0.9341 | 0.9509 | 0.9424 | 0.9609 |
| 0.6219 | 7.0 | 945 | 0.1041 | 0.9516 | 0.9650 | 0.9582 | 0.9720 |
| 0.2085 | 8.0 | 1080 | 0.0992 | 0.9526 | 0.9669 | 0.9597 | 0.9730 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1