small-vanilla-target-conll2003 – AI Model by muhtasham | AlphaNeural AI

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muhtasham/
small-vanilla-target-conll2003

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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small-vanilla-target-conll2003

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1128
Precision: 0.8947
Recall: 0.9165
F1: 0.9055
Accuracy: 0.9782

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: 3e-05
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: constant
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.217	1.14	500	0.0895	0.8414	0.8846	0.8624	0.9725
0.0723	2.28	1000	0.0808	0.8853	0.8975	0.8914	0.9762
0.0427	3.42	1500	0.0807	0.8886	0.9118	0.9001	0.9778
0.0274	4.56	2000	0.0816	0.8983	0.9142	0.9062	0.9790
0.0186	5.69	2500	0.0910	0.8990	0.9201	0.9094	0.9788
0.0132	6.83	3000	0.0933	0.8978	0.9180	0.9078	0.9789
0.0097	7.97	3500	0.0954	0.9025	0.9211	0.9117	0.9798
0.0076	9.11	4000	0.1003	0.9007	0.9221	0.9113	0.9794
0.0058	10.25	4500	0.1037	0.9032	0.9222	0.9126	0.9798
0.005	11.39	5000	0.1128	0.8947	0.9165	0.9055	0.9782

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.8.1.dev0
Tokenizers 0.13.2