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-GoldP_Te
    results: []

vnktrmnb/bert-base-multilingual-cased-FT-TyDiQA-GoldP_Te

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: 0.5179
Train End Logits Accuracy: 0.8477
Train Start Logits Accuracy: 0.8856
Validation Loss: 0.4616
Validation End Logits Accuracy: 0.8570
Validation Start Logits Accuracy: 0.9072
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': 1359, '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
1.4743	0.6319	0.6682	0.5295	0.8351	0.8982	0
0.7342	0.7911	0.8366	0.4560	0.8492	0.9021	1
0.5179	0.8477	0.8856	0.4616	0.8570	0.9072	2

Framework versions

Transformers 4.31.0
TensorFlow 2.12.0
Datasets 2.14.4
Tokenizers 0.13.3