RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-combine-filtered – AI Model by ktgiahieu | AlphaNeural AI

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RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-combine-filtered

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-combine-filtered

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3511
Precision: 0.6276
Recall: 0.5234
F1: 0.5708
Accuracy: 0.8858

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	11	0.7773	0.0	0.0	0.0	0.7228
No log	2.0	22	0.4915	0.4570	0.3617	0.4038	0.8293
No log	3.0	33	0.4246	0.4091	0.3447	0.3741	0.8404
No log	4.0	44	0.3725	0.4899	0.4128	0.4480	0.8659
No log	5.0	55	0.3628	0.6212	0.5234	0.5681	0.8792
No log	6.0	66	0.3492	0.6458	0.5277	0.5808	0.8825
No log	7.0	77	0.3453	0.6337	0.5447	0.5858	0.8875
No log	8.0	88	0.3546	0.6283	0.5106	0.5634	0.8841
No log	9.0	99	0.3491	0.6089	0.5234	0.5629	0.8858
No log	10.0	110	0.3511	0.6276	0.5234	0.5708	0.8858

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3