ag-news-9600-bert-base-uncased – AI Model by Kyle1668 | AlphaNeural AI

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Kyle1668/
ag-news-9600-bert-base-uncased

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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ag-news-twitter-9600-bert-base-uncased

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

F1: 0.9162
Acc: 0.9162
Loss: 0.6033

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: 2e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	F1	Acc	Validation Loss
0.8065	1.0	600	0.9060	0.9059	0.3013
0.2872	2.0	1200	0.9171	0.9170	0.2598
0.2156	3.0	1800	0.9178	0.9184	0.3117
0.1486	4.0	2400	0.9200	0.9197	0.3631
0.0683	5.0	3000	0.9202	0.9201	0.3782
0.045	6.0	3600	0.9186	0.9188	0.4846
0.0218	7.0	4200	0.9155	0.9155	0.5898
0.0245	8.0	4800	0.9162	0.9162	0.6033

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.14.6
Tokenizers 0.14.1