tf_kaggle_llm_qa_model – AI Model by anirbanbanerjee170577 | AlphaNeural AI

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anirbanbanerjee170577/
tf_kaggle_llm_qa_model

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distilbert/distilbert-base-uncased

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anirbanbanerjee170577/tf_kaggle_llm_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: 3.0474
Validation Loss: 3.0542
Epoch: 9

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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 40, '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
4.2592	3.0542	0
3.0553	3.0542	1
3.0336	3.0542	2
3.0477	3.0542	3
3.0463	3.0542	4
3.0493	3.0542	5
3.0523	3.0542	6
3.0568	3.0542	7
3.0599	3.0542	8
3.0474	3.0542	9

Framework versions

Transformers 4.33.0
TensorFlow 2.12.0
Datasets 2.7.0
Tokenizers 0.13.3