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

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

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distilbert-base-uncased-lora-text-classification

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: 0.9635
Accuracy: {'accuracy': 0.888}

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	0.4712	{'accuracy': 0.855}
0.4347	2.0	500	0.4550	{'accuracy': 0.876}
0.4347	3.0	750	0.4948	{'accuracy': 0.885}
0.1809	4.0	1000	0.6488	{'accuracy': 0.885}
0.1809	5.0	1250	0.8407	{'accuracy': 0.888}
0.0747	6.0	1500	0.7641	{'accuracy': 0.892}
0.0747	7.0	1750	0.9308	{'accuracy': 0.888}
0.0174	8.0	2000	1.0031	{'accuracy': 0.885}
0.0174	9.0	2250	0.9573	{'accuracy': 0.885}
0.0067	10.0	2500	0.9635	{'accuracy': 0.888}

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1