my_awesome_qa_model – AI Model by Surju | AlphaNeural AI

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my_awesome_qa_model

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Surju/my_awesome_qa_model

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: 1.2988
Validation Loss: 1.5593
Epoch: 23

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': 800, '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	Validation Loss	Epoch
2.9746	1.7124	0
1.4978	1.5593	1
1.3079	1.5593	2
1.3054	1.5593	3
1.3046	1.5593	4
1.3038	1.5593	5
1.2978	1.5593	6
1.3094	1.5593	7
1.3037	1.5593	8
1.3022	1.5593	9
1.3018	1.5593	10
1.3030	1.5593	11
1.3047	1.5593	12
1.3051	1.5593	13
1.3055	1.5593	14
1.3119	1.5593	15
1.3033	1.5593	16
1.3063	1.5593	17
1.3116	1.5593	18
1.3081	1.5593	19
1.3101	1.5593	20
1.3143	1.5593	21
1.3107	1.5593	22
1.2988	1.5593	23

Framework versions

Transformers 4.30.2
TensorFlow 2.12.0
Datasets 2.13.1
Tokenizers 0.13.3