metadata

license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: silviacamplani/distilbert-uncase-direct-finetuning-ai-ner
    results: []

silviacamplani/distilbert-uncase-direct-finetuning-ai-ner

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 3.1628
Validation Loss: 2.9340
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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 18, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
training_precision: mixed_float16

Training results

Train Loss	Validation Loss	Epoch
3.1628	2.9340	0

Framework versions

Transformers 4.20.1
TensorFlow 2.6.4
Datasets 2.1.0
Tokenizers 0.12.1