README.md

metadata

license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
  - generated_from_keras_callback
model-index:
  - name: aadhistii/tsel-finetune-bert-base-multilingual-cased-2k-formal-v2
    results: []

aadhistii/tsel-finetune-bert-base-multilingual-cased-2k-formal-v2

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.9754
• Validation Loss: 0.8980
• Train Precision: 0.7162
• Train Recall: 0.4951
• Train F1: 0.4870
• Train Accuracy: 0.5824
• Epoch: 0

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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 940, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.9754	0.8980	0.7162	0.4951	0.4870	0.5824	0

Framework versions

• Transformers 4.42.3
• TensorFlow 2.15.0
• Datasets 2.20.0
• Tokenizers 0.19.1