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

Name: distilbert-base-uncased-lora-text-classification
Availability: InStock

peft

safetensors

generated_from_trainer

distilbert/distilbert-base-uncased

adapter

apache-2.0

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distilbert-base-uncased-lora-text-classification

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

Loss: 1.0476
Accuracy: {'accuracy': 0.878}

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.3883	{'accuracy': 0.874}
0.436	2.0	500	0.4803	{'accuracy': 0.863}
0.436	3.0	750	0.7892	{'accuracy': 0.843}
0.1824	4.0	1000	0.7530	{'accuracy': 0.874}
0.1824	5.0	1250	0.9025	{'accuracy': 0.876}
0.0705	6.0	1500	0.9245	{'accuracy': 0.872}
0.0705	7.0	1750	0.9648	{'accuracy': 0.878}
0.0244	8.0	2000	1.0001	{'accuracy': 0.877}
0.0244	9.0	2250	1.0236	{'accuracy': 0.88}
0.0045	10.0	2500	1.0476	{'accuracy': 0.878}

Framework versions

PEFT 0.14.0
Transformers 4.48.0
Pytorch 2.5.1+cu118
Datasets 3.2.0
Tokenizers 0.21.0

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

distilbert-base-uncased-lora-text-classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

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