codebert-base-finetuned-code-ner – AI Model by mrm8488 | AlphaNeural AI

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mrm8488/
codebert-base-finetuned-code-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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codebert-base-finetuned-code-ner

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

Loss: 0.3522
Precision: 0.6297
Recall: 0.6417
F1: 0.6356
Accuracy: 0.9185

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: 64
eval_batch_size: 64
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	191	0.4601	0.4861	0.4578	0.4715	0.8853
No log	2.0	382	0.3989	0.5806	0.5243	0.5510	0.8996
0.5081	3.0	573	0.3547	0.5723	0.6017	0.5866	0.9059
0.5081	4.0	764	0.3507	0.6161	0.6115	0.6138	0.9135
0.5081	5.0	955	0.3412	0.6299	0.6252	0.6276	0.9161
0.2299	6.0	1146	0.3418	0.6162	0.6465	0.6310	0.9175
0.2299	7.0	1337	0.3497	0.6288	0.6287	0.6287	0.9175
0.1618	8.0	1528	0.3474	0.6340	0.6397	0.6368	0.9189
0.1618	9.0	1719	0.3501	0.6262	0.6432	0.6346	0.9179
0.1618	10.0	1910	0.3522	0.6297	0.6417	0.6356	0.9185

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1