metadata

license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
  - generated_from_keras_callback
model-index:
  - name: vnktrmnb/bert-base-multilingual-cased-FT-TyDiQA_PPQ
    results: []

vnktrmnb/bert-base-multilingual-cased-FT-TyDiQA_PPQ

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: 0.1315
Train End Logits Accuracy: 0.9554
Train Start Logits Accuracy: 0.9654
Validation Loss: 0.6059
Validation End Logits Accuracy: 0.8518
Validation Start Logits Accuracy: 0.9021
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': '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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2676, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train End Logits Accuracy	Train Start Logits Accuracy	Validation Loss	Validation End Logits Accuracy	Validation Start Logits Accuracy	Epoch
0.4322	0.8625	0.8874	0.5311	0.8621	0.9008	0
0.2279	0.9238	0.9391	0.5657	0.8402	0.9046	1
0.1315	0.9554	0.9654	0.6059	0.8518	0.9021	2

Framework versions

Transformers 4.31.0
TensorFlow 2.12.0
Datasets 2.14.4
Tokenizers 0.13.3