mahabharahta/dok-ner-bert-base-multilingual-cased
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0007
- Validation Loss: 0.0002
- Train Precision: 1.0
- Train Recall: 1.0
- Train F1: 1.0
- Train Accuracy: 1.0
- Epoch: 2
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3279, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
---|---|---|---|---|---|---|
0.0530 | 0.0007 | 0.9998 | 0.9999 | 0.9998 | 1.0000 | 0 |
0.0014 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 1 |
0.0007 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 2 |
Framework versions
- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.2
- Tokenizers 0.19.1
- Downloads last month
- 5
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for mahabharahta/dok-ner-bert-base-multilingual-cased
Base model
google-bert/bert-base-multilingual-cased