workornot – AI Model by MaggieZhang | AlphaNeural AI

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MaggieZhang/
workornot

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distilbert/distilbert-base-uncased

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workornot

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3372
Accuracy: 0.856

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
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	125	0.6385	0.787
No log	2.0	250	0.5578	0.808
No log	3.0	375	0.4489	0.818
0.5423	4.0	500	0.3610	0.843
0.5423	5.0	625	0.3374	0.855
0.5423	6.0	750	0.3365	0.854
0.5423	7.0	875	0.3331	0.857
0.3101	8.0	1000	0.3359	0.857
0.3101	9.0	1125	0.3377	0.855
0.3101	10.0	1250	0.3372	0.856

Framework versions

PEFT 0.8.2
Transformers 4.39.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2