FPC_model – AI Model by anth0nyhak1m | AlphaNeural AI

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FPC_model

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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FPC_model

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

Loss: 0.4029
Accuracy: 0.9153

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: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	285	1.1683	0.7397
1.5827	2.0	570	0.6301	0.8481
1.5827	3.0	855	0.5046	0.8755
0.4453	4.0	1140	0.4156	0.8941
0.4453	5.0	1425	0.3790	0.9153
0.1964	6.0	1710	0.3949	0.9078
0.1964	7.0	1995	0.3969	0.9153
0.1072	8.0	2280	0.4002	0.9153
0.0611	9.0	2565	0.4027	0.9141
0.0611	10.0	2850	0.4029	0.9153

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.0
Tokenizers 0.13.3