RoBERTa_conll_epoch_4 – AI Model by ICT2214Team7 | AlphaNeural AI

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ICT2214Team7/
RoBERTa_conll_epoch_4

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token-classification

generated_from_trainer

distilbert/distilroberta-base

autotrain_compatible

endpoints_compatible

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RoBERTa_conll_epoch_4

This model is a fine-tuned version of distilroberta-base on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0595
Precision: 0.9446
Recall: 0.9586
F1: 0.9516
Accuracy: 0.9885

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0785	1.0	1756	0.0667	0.9131	0.9335	0.9232	0.9835
0.0379	2.0	3512	0.0619	0.9341	0.9445	0.9392	0.9864
0.0207	3.0	5268	0.0609	0.9424	0.9529	0.9476	0.9872
0.0105	4.0	7024	0.0595	0.9446	0.9586	0.9516	0.9885

Framework versions

Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1