You can deploy this model and start earning money today!

badokorach/
distilbert-base-cased-160923

Name: distilbert-base-cased-160923
Availability: InStock

transformers

bert

question-answering

generated_from_keras_callback

badokorach/distilbert-base-cased-160923

finetune

endpoints_compatible

Views

No views yet

badokorach/distilbert-base-cased-160923

This model is a fine-tuned version of badokorach/distilbert-base-cased-160923 on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.0084
Validation Loss: 0.0
Epoch: 28

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': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1946, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 4, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.02}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
training_precision: mixed_float16

Training results

Train Loss	Validation Loss	Epoch
0.0655	0.0	0
0.1225	0.0	1
0.0648	0.0	2
0.0527	0.0	3
0.0653	0.0	4
0.0456	0.0	5
0.0482	0.0	6
0.0318	0.0	7
0.0183	0.0	8
0.0237	0.0	9
0.0146	0.0	10
0.0231	0.0	11
0.0115	0.0	12
0.0161	0.0	13
0.0129	0.0	14
0.0162	0.0	15
0.0118	0.0	16
0.0109	0.0	17
0.0097	0.0	18
0.0070	0.0	19
0.0073	0.0	20
0.0099	0.0	21
0.0067	0.0	22
0.0037	0.0	23
0.0041	0.0	24
0.0082	0.0	25
0.0037	0.0	26
0.0054	0.0	27
0.0084	0.0	28

Framework versions

Transformers 4.33.2
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.13.3