bert-base-phia-test – AI Model by reiffd | AlphaNeural AI

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reiffd/
bert-base-phia-test

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-base-phia-test

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

Loss: 0.0910
F1: 0.9900

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: 5e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	50	1.4259	0.5356
No log	2.0	100	0.9857	0.6872
No log	3.0	150	0.6589	0.7432
1.2595	4.0	200	0.4964	0.7834
1.2595	5.0	250	0.3924	0.8645
1.2595	6.0	300	0.2486	0.9424
1.2595	7.0	350	0.1698	0.9673
0.3376	8.0	400	0.1360	0.9763
0.3376	9.0	450	0.1050	0.9763
0.3376	10.0	500	0.0910	0.9900

Framework versions

Transformers 4.42.3
Pytorch 2.3.1
Datasets 2.20.0
Tokenizers 0.19.1