distilbert-base-uncased-lora-text-classification – AI Model by Sube126 | AlphaNeural AI

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Sube126/
distilbert-base-uncased-lora-text-classification

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distilbert/distilbert-base-uncased

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distilbert-base-uncased-lora-text-classification

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: 1.0362
Accuracy: {'accuracy': 0.866}

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: 4
eval_batch_size: 4
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	250	0.5633	{'accuracy': 0.822}
0.4445	2.0	500	0.5395	{'accuracy': 0.85}
0.4445	3.0	750	0.7314	{'accuracy': 0.844}
0.3104	4.0	1000	0.6346	{'accuracy': 0.867}
0.3104	5.0	1250	0.7909	{'accuracy': 0.854}
0.1899	6.0	1500	0.8945	{'accuracy': 0.872}
0.1899	7.0	1750	0.9758	{'accuracy': 0.866}
0.0805	8.0	2000	1.0404	{'accuracy': 0.865}
0.0805	9.0	2250	1.0483	{'accuracy': 0.861}
0.0581	10.0	2500	1.0362	{'accuracy': 0.866}

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1