my_awesome_wnut_model_roberta – AI Model by julieou | AlphaNeural AI

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julieou/
my_awesome_wnut_model_roberta

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token-classification

generated_from_trainer

distilbert/distilroberta-base

endpoints_compatible

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my_awesome_wnut_model_roberta

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

Loss: 0.3147
Precision: 0.6358
Recall: 0.4578
F1: 0.5323
Accuracy: 0.9521

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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2470	0.5175	0.3967	0.4491	0.9419
No log	2.0	426	0.2284	0.5582	0.4532	0.5003	0.9493
0.1690	3.0	639	0.2092	0.5175	0.5070	0.5122	0.9505
0.1690	4.0	852	0.2480	0.5602	0.5005	0.5286	0.9501
0.0475	5.0	1065	0.2692	0.6267	0.4745	0.5401	0.9523
0.0475	6.0	1278	0.2808	0.6317	0.4467	0.5233	0.9525
0.0475	7.0	1491	0.3147	0.6358	0.4578	0.5323	0.9521

Framework versions

Transformers 5.15.0
Pytorch 2.11.0+cpu
Datasets 4.0.0
Tokenizers 0.22.2