output – AI Model by BashirRP | AlphaNeural AI

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output

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text-classification

generated_from_trainer

microsoft/deberta-base

autotrain_compatible

endpoints_compatible

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output

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

Loss: 0.0014
F1: 0.9009
Accuracy: 0.89

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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.3529	0.16	10	0.2584	0.6667	0.5
0.2348	0.32	20	0.0989	0.6667	0.5
0.0492	0.48	30	0.0314	0.9615	0.96
0.0336	0.64	40	0.0132	0.6849	0.54
0.0185	0.8	50	0.0345	0.6667	0.5
0.0114	0.96	60	0.0490	0.9524	0.95
0.0118	1.12	70	0.0235	0.7042	0.58
0.01	1.28	80	0.0352	0.7299	0.63
0.0061	1.44	90	0.0195	0.8	0.75
0.0067	1.6	100	0.0108	0.8547	0.83
0.0055	1.76	110	0.0186	0.7874	0.73
0.0052	1.92	120	0.0141	0.9174	0.91

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0