ernietask1 – AI Model by MohammadKarami | AlphaNeural AI

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MohammadKarami/
ernietask1

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text-classification

generated_from_trainer

susnato/ernie-m-base_pytorch

autotrain_compatible

endpoints_compatible

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Model

This model is a fine-tuned version of susnato/ernie-m-base_pytorch on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6189
F1: 0.9294

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.2019	1.0	1500	0.1825	0.9304
0.1199	2.0	3000	0.3103	0.8986
0.085	3.0	4500	0.2546	0.9268
0.0516	4.0	6000	0.3140	0.9387
0.0281	5.0	7500	0.6603	0.9022
0.0142	6.0	9000	0.8612	0.8931
0.0068	7.0	10500	0.5700	0.9332
0.002	8.0	12000	0.6189	0.9294

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1