my_awesome_wnut_model – AI Model by SeaniMoxxu | AlphaNeural AI

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SeaniMoxxu/
my_awesome_wnut_model

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token-classification

generated_from_trainer

almanach/camembert-base

autotrain_compatible

endpoints_compatible

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my_awesome_wnut_model

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

Loss: 0.0122
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.9985

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	160	0.0387	0.0	0.0	0.0	0.9984
No log	2.0	320	0.0267	0.0	0.0	0.0	0.9985
No log	3.0	480	0.0206	0.0	0.0	0.0	0.9986
0.0675	4.0	640	0.0164	0.0	0.0	0.0	0.9987
0.0675	5.0	800	0.0143	0.0	0.0	0.0	0.9987
0.0675	6.0	960	0.0134	0.0	0.0	0.0	0.9985
0.0141	7.0	1120	0.0129	0.0	0.0	0.0	0.9984
0.0141	8.0	1280	0.0125	0.0	0.0	0.0	0.9985
0.0141	9.0	1440	0.0124	0.0	0.0	0.0	0.9985
0.0085	10.0	1600	0.0122	0.0	0.0	0.0	0.9985

Framework versions

Transformers 4.56.0
Pytorch 2.8.0+cu129
Datasets 4.0.0
Tokenizers 0.22.0