bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27 – AI Model by ali2066 | AlphaNeural AI

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ali2066/
bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-uncased_token_itr0_0.0001_all_01_03_2022-04_48_27

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2899
Precision: 0.3170
Recall: 0.5261
F1: 0.3956
Accuracy: 0.8799

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:

learning_rate: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	30	0.2912	0.2752	0.4444	0.3400	0.8730
No log	2.0	60	0.2772	0.4005	0.4589	0.4277	0.8911
No log	3.0	90	0.2267	0.3642	0.5281	0.4311	0.9043
No log	4.0	120	0.2129	0.3617	0.5455	0.4350	0.9140
No log	5.0	150	0.2399	0.3797	0.5556	0.4511	0.9114

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3