bert-base-uncased-wnut_17 – AI Model by yefo-ufpe | AlphaNeural AI

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bert-base-uncased-wnut_17

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google-bert/bert-base-uncased

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bert-base-uncased-wnut_17

This model is a fine-tuned version of google-bert/bert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:

Loss: 0.2870
Precision: 0.4802
Recall: 0.2132
F1: 0.2953
Accuracy: 0.9366

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: 16
eval_batch_size: 16
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	Precision	Recall	F1	Accuracy
No log	1.0	213	0.4305	1.0	0.0	0.0	0.9256
No log	2.0	426	0.3568	0.0	0.0	0.0	0.9256
0.496	3.0	639	0.3379	0.3495	0.0334	0.0609	0.9277
0.496	4.0	852	0.3166	0.3824	0.1205	0.1832	0.9321
0.1935	5.0	1065	0.3034	0.3907	0.1705	0.2374	0.9343
0.1935	6.0	1278	0.2956	0.4313	0.1863	0.2602	0.9353
0.1935	7.0	1491	0.2941	0.4700	0.1891	0.2697	0.9357
0.1717	8.0	1704	0.2960	0.4874	0.1965	0.2801	0.9363
0.1717	9.0	1917	0.2882	0.4797	0.2076	0.2898	0.9364
0.1594	10.0	2130	0.2870	0.4802	0.2132	0.2953	0.9366

Framework versions

PEFT 0.12.1.dev0
Transformers 4.45.0.dev0
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1