word-detection-1-1 – AI Model by charisgao | AlphaNeural AI

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charisgao/
word-detection-1-1

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token-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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model

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

Loss: 0.2755
Precision: 0.4545
Recall: 0.0935
F1: 0.1550
Accuracy: 0.9109

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: 4
eval_batch_size: 4
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.3038	0.4292	100	0.2895	0.0	0.0	0.0	0.9125
0.2835	0.8584	200	0.2731	0.0	0.0	0.0	0.9125
0.2383	1.2876	300	0.2710	0.5606	0.0384	0.0719	0.9132
0.2385	1.7167	400	0.2685	0.6786	0.0197	0.0383	0.9134
0.2356	2.1459	500	0.2734	0.4466	0.0955	0.1574	0.9105
0.2067	2.5751	600	0.2719	0.4703	0.0987	0.1631	0.9114

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0