trainer – AI Model by indiana500 | AlphaNeural AI

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indiana500/
trainer

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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trainer

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: 0.6671
Accuracy: {'accuracy': 0.6136936111747194}

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: 0.001
train_batch_size: 20
eval_batch_size: 20
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
0.6681	1.0	1020	0.6671	{'accuracy': 0.6136936111747194}
0.667	2.0	2040	0.6671	{'accuracy': 0.6136936111747194}
0.6697	3.0	3060	0.6692	{'accuracy': 0.6136936111747194}
0.6663	4.0	4080	0.6673	{'accuracy': 0.6136936111747194}
0.6655	5.0	5100	0.6671	{'accuracy': 0.6136936111747194}
0.669	6.0	6120	0.6671	{'accuracy': 0.6136936111747194}
0.6667	7.0	7140	0.6671	{'accuracy': 0.6136936111747194}
0.6684	8.0	8160	0.6671	{'accuracy': 0.6136936111747194}
0.6651	9.0	9180	0.6671	{'accuracy': 0.6136936111747194}
0.6669	10.0	10200	0.6671	{'accuracy': 0.6136936111747194}

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2